Volumetric imaging of the 3D orientation of cellular structures with a polarized fluorescence light-sheet microscope

Συγγραφείς: Chandler, Talon, Guo, Min, Su, Yijun, Chen, Jiji, Wu, Yicong, Liu, Junyu, Agashe, Atharva, Fischer, Robert, Mehta, Shalin B., Kumar, Abhishek, Baskin, Tobias, Jaumouillé, Valentin, Liu, Huafeng, Swaminathan, Vinay, Nain, Amrinder S., Oldenbourg, Rudolf, La Riviere, Patrick J., Shroff, Hari

Συνεισφορές: Lund University, Profile areas and other strong research environments, Lund University Profile areas, LU Profile Area: Light and Materials, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Lunds universitets profilområden, LU profilområde: Ljus och material, Originator, Lund University, Faculty of Engineering, LTH, LTH Profile areas, LTH Profile Area: Photon Science and Technology, Lunds universitet, Lunds Tekniska Högskola, LTH profilområden, LTH profilområde: Avancerade ljuskällor, Originator, Lund University, Faculty of Engineering, LTH, LTH Profile areas, LTH Profile Area: Nanoscience and Semiconductor Technology, Lunds universitet, Lunds Tekniska Högskola, LTH profilområden, LTH profilområde: Nanovetenskap och halvledarteknologi, Originator, Lund University, Profile areas and other strong research environments, Strategic research areas (SRA), NanoLund: Centre for Nanoscience, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Strategiska forskningsområden (SFO), NanoLund: Centre for Nanoscience, Originator, Lund University, Profile areas and other strong research environments, Other Strong Research Environments, LUCC: Lund University Cancer Centre, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Övriga starka forskningsmiljöer, LUCC: Lunds universitets cancercentrum, Originator, Lund University, Faculty of Medicine, Department of Clinical Sciences, Lund, Section I, Cell mechanobiology, Lunds universitet, Medicinska fakulteten, Institutionen för kliniska vetenskaper, Lund, Sektion I, Cellmekanobiologi, Originator, Lund University, Faculty of Medicine, WCMM-Wallenberg Centre for Molecular Medicine, Lunds universitet, Medicinska fakulteten, WCMM- Wallenberg center för molekylär medicinsk forskning, Originator

Πηγή: Proceedings of the National Academy of Sciences. 122(8):1-12

Θεματικοί όροι: Natural Sciences, Physical Sciences, Biophysics, Naturvetenskap, Fysik, Biofysik, Computer and Information Sciences, Computer graphics and computer vision, Data- och informationsvetenskap (Datateknik), Datorgrafik och datorseende

Σύνδεσμος πρόσβασης: https://doi.org/10.1073/pnas.2406679122

Pixel-Perfect Structure-From-Motion With Featuremetric Refinement

Συγγραφείς: Sarlin, Paul Edouard, Lindenberger, Philipp, Larsson, Viktor, Pollefeys, Marc

Συνεισφορές: Lund University, Faculty of Engineering, LTH, LTH Profile areas, LTH Profile Area: AI and Digitalization, Lunds universitet, Lunds Tekniska Högskola, LTH profilområden, LTH profilområde: AI och digitalisering, Originator, Lund University, Faculty of Science, Centre for Mathematical Sciences, Research groups at the Centre for Mathematical Sciences, Mathematical Imaging Group, Lunds universitet, Naturvetenskapliga fakulteten, Matematikcentrum, Forskargrupper vid Matematikcentrum, Mathematical Imaging Group, Originator, Lund University, Faculty of Science, Centre for Mathematical Sciences, Mathematics (Faculty of Engineering), Computer Vision and Machine Learning, Lunds universitet, Naturvetenskapliga fakulteten, Matematikcentrum, Matematik LTH, Datorseende och maskininlärning, Originator, Lund University, Profile areas and other strong research environments, Lund University Profile areas, LU Profile Area: Natural and Artificial Cognition, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Lunds universitets profilområden, LU profilområde: Naturlig och artificiell kognition, Originator, Lund University, Profile areas and other strong research environments, Strategic research areas (SRA), ELLIIT: the Linköping-Lund initiative on IT and mobile communication, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Strategiska forskningsområden (SFO), ELLIIT: the Linköping-Lund initiative on IT and mobile communication, Originator

Πηγή: IEEE Transactions on Pattern Analysis and Machine Intelligence. 47(5):3298-3309

Θεματικοί όροι: Natural Sciences, Computer and Information Sciences, Computer graphics and computer vision, Naturvetenskap, Data- och informationsvetenskap (Datateknik), Datorgrafik och datorseende

Σύνδεσμος πρόσβασης: https://doi.org/10.1109/TPAMI.2023.3237269

Breast cancer classification in point-of-care ultrasound imaging—the impact of training data

Συγγραφείς: Karlsson, Jennie, Arvidsson, Ida, Sahlin, Freja, Åström, Kalle, Overgaard, Niels Christian, Lång, Kristina, Heyden, Anders

Συνεισφορές: Lund University, Faculty of Science, Centre for Mathematical Sciences, Mathematics (Faculty of Engineering), Computer Vision and Machine Learning, Lunds universitet, Naturvetenskapliga fakulteten, Matematikcentrum, Matematik LTH, Datorseende och maskininlärning, Originator, Lund University, Profile areas and other strong research environments, Lund University Profile areas, LU Profile Area: Natural and Artificial Cognition, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Lunds universitets profilområden, LU profilområde: Naturlig och artificiell kognition, Originator, Lund University, Profile areas and other strong research environments, Strategic research areas (SRA), eSSENCE: The e-Science Collaboration, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Strategiska forskningsområden (SFO), eSSENCE: The e-Science Collaboration, Originator, Lund University, Profile areas and other strong research environments, Strategic research areas (SRA), ELLIIT: the Linköping-Lund initiative on IT and mobile communication, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Strategiska forskningsområden (SFO), ELLIIT: the Linköping-Lund initiative on IT and mobile communication, Originator, Lund University, Profile areas and other strong research environments, Lund University Profile areas, LU Profile Area: Proactive Ageing, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Lunds universitets profilområden, LU profilområde: Proaktivt åldrande, Originator, Lund University, Faculty of Engineering, LTH, LTH Profile areas, LTH Profile Area: AI and Digitalization, Lunds universitet, Lunds Tekniska Högskola, LTH profilområden, LTH profilområde: AI och digitalisering, Originator, Lund University, Profile areas and other strong research environments, Lund University Profile areas, LU Profile Area: Nature-based future solutions, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Lunds universitets profilområden, LU profilområde: Naturbaserade framtidslösningar, Originator, Lund University, Profile areas and other strong research environments, Lund University Profile areas, LU Profile Area: Light and Materials, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Lunds universitets profilområden, LU profilområde: Ljus och material, Originator, Lund University, Faculty of Engineering, LTH, LTH Profile areas, LTH Profile Area: Engineering Health, Lunds universitet, Lunds Tekniska Högskola, LTH profilområden, LTH profilområde: Teknik för hälsa, Originator, Lund University, Faculty of Medicine, Department of Clinical Sciences, Lund, Section V, Diagnostic Radiology, (Lund), Stroke Imaging Research group, Lunds universitet, Medicinska fakulteten, Institutionen för kliniska vetenskaper, Lund, Sektion V, Diagnostisk radiologi, Lund, Stroke Imaging Research group, Originator, Lund University, Faculty of Science, Centre for Mathematical Sciences, Research groups at the Centre for Mathematical Sciences, Mathematical Imaging Group, Lunds universitet, Naturvetenskapliga fakulteten, Matematikcentrum, Forskargrupper vid Matematikcentrum, Mathematical Imaging Group, Originator, Lund University, Faculty of Science, Centre for Mathematical Sciences, Research groups at the Centre for Mathematical Sciences, Partial differential equations, Lunds universitet, Naturvetenskapliga fakulteten, Matematikcentrum, Forskargrupper vid Matematikcentrum, Partiella differentialekvationer, Originator, Lund University, Profile areas and other strong research environments, Other Strong Research Environments, LUCC: Lund University Cancer Centre, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Övriga starka forskningsmiljöer, LUCC: Lunds universitets cancercentrum, Originator, Lund University, Faculty of Medicine, Department of Translational Medicine, Radiology Diagnostics, Malmö, Lunds universitet, Medicinska fakulteten, Institutionen för translationell medicin, Diagnostisk radiologi, Malmö, Originator

Πηγή: Journal of Medical Imaging. 12(1):1-16

Θεματικοί όροι: Natural Sciences, Computer and Information Sciences, Computer graphics and computer vision, Naturvetenskap, Data- och informationsvetenskap (Datateknik), Datorgrafik och datorseende, Engineering and Technology, Medical Engineering, Medical Imaging, Teknik, Medicinteknik, Medicinsk bildvetenskap

Σύνδεσμος πρόσβασης: https://doi.org/10.1117/1.JMI.12.1.014502

An annotated high-content fluorescence microscopy dataset with EGFP-Galectin-3-stained cells and manually labelled outlines

Συγγραφείς: Rashed, Salma Kazemi, Arvidsson, Malou, Ahmed, Rafsan, Aits, Sonja

Συνεισφορές: Lund University, Faculty of Engineering, LTH, LTH Profile areas, LTH Profile Area: Engineering Health, Lunds universitet, Lunds Tekniska Högskola, LTH profilområden, LTH profilområde: Teknik för hälsa, Originator, Lund University, Profile areas and other strong research environments, Lund University Profile areas, LU Profile Area: Natural and Artificial Cognition, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Lunds universitets profilområden, LU profilområde: Naturlig och artificiell kognition, Originator, Lund University, Faculty of Medicine, Department of Experimental Medical Science, Cell Death, Lysosomes and Artificial Intelligence, Lunds universitet, Medicinska fakulteten, Institutionen för experimentell medicinsk vetenskap, Celldöd, Lysosomer och Artificiell Intelligens, Originator, Lund University, Profile areas and other strong research environments, Lund University Profile areas, LU Profile Area: Proactive Ageing, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Lunds universitets profilområden, LU profilområde: Proaktivt åldrande, Originator, Lund University, Profile areas and other strong research environments, Lund University Profile areas, LU Profile Area: Nature-based future solutions, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Lunds universitets profilområden, LU profilområde: Naturbaserade framtidslösningar, Originator, Lund University, Faculty of Engineering, LTH, LTH Profile areas, LTH Profile Area: AI and Digitalization, Lunds universitet, Lunds Tekniska Högskola, LTH profilområden, LTH profilområde: AI och digitalisering, Originator, Lund University, Profile areas and other strong research environments, Strategic research areas (SRA), EpiHealth: Epidemiology for Health, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Strategiska forskningsområden (SFO), EpiHealth: Epidemiology for Health, Originator, Lund University, Profile areas and other strong research environments, Other Strong Research Environments, LUCC: Lund University Cancer Centre, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Övriga starka forskningsmiljöer, LUCC: Lunds universitets cancercentrum, Originator, Lund University, Profile areas and other strong research environments, Strategic research areas (SRA), eSSENCE: The e-Science Collaboration, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Strategiska forskningsområden (SFO), eSSENCE: The e-Science Collaboration, Originator

Πηγή: Data in Brief. 58:1-9

Θεματικοί όροι: Natural Sciences, Computer and Information Sciences, Computer graphics and computer vision, Naturvetenskap, Data- och informationsvetenskap (Datateknik), Datorgrafik och datorseende

Σύνδεσμος πρόσβασης: https://doi.org/10.1016/j.dib.2024.111148

X-ray nano-holotomography reconstruction with simultaneous probe retrieval

Συγγραφείς: Nikitin, Viktor, Carlsson, Marcus, Gürsoy, Doga, Mokso, Rajmund, Cloetens, Peter

Συνεισφορές: Lund University, Faculty of Science, Centre for Mathematical Sciences, Mathematics (Faculty of Sciences), Lunds universitet, Naturvetenskapliga fakulteten, Matematikcentrum, Matematik (naturvetenskapliga fakulteten), Originator, Lund University, Profile areas and other strong research environments, Strategic research areas (SRA), eSSENCE: The e-Science Collaboration, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Strategiska forskningsområden (SFO), eSSENCE: The e-Science Collaboration, Originator

Πηγή: Optics Express. 32(23):41905-41924

Θεματικοί όροι: Natural Sciences, Physical Sciences, Atom and Molecular Physics and Optics, Naturvetenskap, Fysik, Atom- och molekylfysik och optik (Här ingår: Kemisk fysik, kvantoptik), Computer and Information Sciences, Computer graphics and computer vision, Data- och informationsvetenskap (Datateknik), Datorgrafik och datorseende, Subatomic Physics, Subatomär fysik

Σύνδεσμος πρόσβασης: https://doi.org/10.1364/OE.537341

LuViRA Dataset Validation and Discussion: Comparing Vision, Radio, and Audio Sensors for Indoor Localization

Συγγραφείς: Yaman, Ilayda, Tian, Guoda, Tegler, Erik, Gulin, Jens, Challa, Nikhil, Tufvesson, Fredrik, Edfors, Ove, Åström, Kalle, Malkowsky, Steffen, Liu, Liang

Συνεισφορές: Lund University, Faculty of Engineering, LTH, Departments at LTH, Department of Electrical and Information Technology, Integrated Electronic Systems, Lunds universitet, Lunds Tekniska Högskola, Institutioner vid LTH, Institutionen för elektro- och informationsteknik, Integrerade elektroniksystem, Originator, Lund University, Faculty of Engineering, LTH, LTH Profile areas, LTH Profile Area: AI and Digitalization, Lunds universitet, Lunds Tekniska Högskola, LTH profilområden, LTH profilområde: AI och digitalisering, Originator, Lund University, Profile areas and other strong research environments, Strategic research areas (SRA), ELLIIT: the Linköping-Lund initiative on IT and mobile communication, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Strategiska forskningsområden (SFO), ELLIIT: the Linköping-Lund initiative on IT and mobile communication, Originator, Lund University, Faculty of Engineering, LTH, Departments at LTH, Department of Electrical and Information Technology, Communications Engineering, Lunds universitet, Lunds Tekniska Högskola, Institutioner vid LTH, Institutionen för elektro- och informationsteknik, Kommunikationsteknologi, Originator, Lund University, Faculty of Science, Centre for Mathematical Sciences, Mathematics (Faculty of Engineering), Computer Vision and Machine Learning, Lunds universitet, Naturvetenskapliga fakulteten, Matematikcentrum, Matematik LTH, Datorseende och maskininlärning, Originator, Lund University, Profile areas and other strong research environments, Lund University Profile areas, LU Profile Area: Natural and Artificial Cognition, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Lunds universitets profilområden, LU profilområde: Naturlig och artificiell kognition, Originator, Lund University, Faculty of Engineering, LTH, Departments at LTH, Department of Electrical and Information Technology, Lunds universitet, Lunds Tekniska Högskola, Institutioner vid LTH, Institutionen för elektro- och informationsteknik, Originator, Lund University, Profile areas and other strong research environments, Lund University Profile areas, LU Profile Area: Light and Materials, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Lunds universitets profilområden, LU profilområde: Ljus och material, Originator, Lund University, Profile areas and other strong research environments, Lund University Profile areas, LU Profile Area: Proactive Ageing, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Lunds universitets profilområden, LU profilområde: Proaktivt åldrande, Originator, Lund University, Faculty of Engineering, LTH, LTH Profile areas, LTH Profile Area: Engineering Health, Lunds universitet, Lunds Tekniska Högskola, LTH profilområden, LTH profilområde: Teknik för hälsa, Originator, Lund University, Faculty of Medicine, Department of Clinical Sciences, Lund, Section V, Diagnostic Radiology, (Lund), Stroke Imaging Research group, Lunds universitet, Medicinska fakulteten, Institutionen för kliniska vetenskaper, Lund, Sektion V, Diagnostisk radiologi, Lund, Stroke Imaging Research group, Originator, Lund University, Profile areas and other strong research environments, Strategic research areas (SRA), eSSENCE: The e-Science Collaboration, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Strategiska forskningsområden (SFO), eSSENCE: The e-Science Collaboration, Originator, Lund University, Faculty of Science, Centre for Mathematical Sciences, Research groups at the Centre for Mathematical Sciences, Mathematical Imaging Group, Lunds universitet, Naturvetenskapliga fakulteten, Matematikcentrum, Forskargrupper vid Matematikcentrum, Mathematical Imaging Group, Originator, Lund University, Faculty of Engineering, LTH, LTH Profile areas, LTH Profile Area: Nanoscience and Semiconductor Technology, Lunds universitet, Lunds Tekniska Högskola, LTH profilområden, LTH profilområde: Nanovetenskap och halvledarteknologi, Originator

Πηγή: IEEE Journal of Indoor and Seamless Positioning and Navigation. :240-250

Θεματικοί όροι: Natural Sciences, Computer and Information Sciences, Computer graphics and computer vision, Naturvetenskap, Data- och informationsvetenskap (Datateknik), Datorgrafik och datorseende

Σύνδεσμος πρόσβασης: https://doi.org/10.1109/JISPIN.2024.3429110

RAMSES-yOMP: Performance Optimizations for the Astrophysical Hydrodynamic Simulation Code RAMSES

Συγγραφείς: Han, San, Dubois, Yohan, Lee, Jaehyun, Kim, Juhan, Cadiou, Corentin, Yi, Sukyoung K.

Συνεισφορές: Lund University, Faculty of Science, Department of Physics, Astrophysics, Lunds universitet, Naturvetenskapliga fakulteten, Fysiska institutionen, Astrofysik, Originator

Πηγή: Astrophysical Journal. 978(1)

Θεματικοί όροι: Natural Sciences, Physical Sciences, Fusion, Plasma and Space Physics, Naturvetenskap, Fysik, plasma och rymdfysik, Computer and Information Sciences, Computer graphics and computer vision, Data- och informationsvetenskap (Datateknik), Datorgrafik och datorseende, Other Physics Topics, Annan fysik

Σύνδεσμος πρόσβασης: https://doi.org/10.3847/1538-4357/ad98f4

Reusability report: Unpaired deep-learning approaches for holographic image

Συγγραφείς: Zhang, Yuhe, Ritschel, Tobias, Villanueva Perez, Pablo

Συνεισφορές: Lund University, Faculty of Science, Department of Physics, Synchrotron Radiation Research, Lunds universitet, Naturvetenskapliga fakulteten, Fysiska institutionen, Synkrotronljusfysik, Originator, Lund University, Profile areas and other strong research environments, Strategic research areas (SRA), NanoLund: Centre for Nanoscience, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Strategiska forskningsområden (SFO), NanoLund: Centre for Nanoscience, Originator, Lund University, Faculty of Engineering, LTH, LTH Profile areas, LTH Profile Area: Nanoscience and Semiconductor Technology, Lunds universitet, Lunds Tekniska Högskola, LTH profilområden, LTH profilområde: Nanovetenskap och halvledarteknologi, Originator, Lund University, Profile areas and other strong research environments, Lund University Profile areas, LU Profile Area: Light and Materials, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Lunds universitets profilområden, LU profilområde: Ljus och material, Originator, Lund University, Faculty of Engineering, LTH, LTH Profile areas, LTH Profile Area: Photon Science and Technology, Lunds universitet, Lunds Tekniska Högskola, LTH profilområden, LTH profilområde: Avancerade ljuskällor, Originator

Πηγή: Nature Machine Intelligence Advancing X-ray imaging with deep learning. 6(3):284-290

Θεματικοί όροι: Natural Sciences, Physical Sciences, Atom and Molecular Physics and Optics, Naturvetenskap, Fysik, Atom- och molekylfysik och optik (Här ingår: Kemisk fysik, kvantoptik), Computer and Information Sciences, Computer graphics and computer vision, Data- och informationsvetenskap (Datateknik), Datorgrafik och datorseende

Σύνδεσμος πρόσβασης: https://doi.org/10.1038/s42256-024-00798-7

Vanilla Bayesian Optimization Performs Great in High Dimensions

Συγγραφείς: Hvarfner, Carl, Hellsten, Erik O., Nardi, Luigi

Συνεισφορές: Lund University, Profile areas and other strong research environments, Strategic research areas (SRA), ELLIIT: the Linköping-Lund initiative on IT and mobile communication, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Strategiska forskningsområden (SFO), ELLIIT: the Linköping-Lund initiative on IT and mobile communication, Originator, Lund University, Faculty of Engineering, LTH, Departments at LTH, Department of Computer Science, Robotics and Semantic Systems, Lunds universitet, Lunds Tekniska Högskola, Institutioner vid LTH, Institutionen för datavetenskap, Robotik och Semantiska System, Originator, Lund University, Faculty of Science, Centre for Mathematical Sciences, Mathematics (Faculty of Engineering), Lunds universitet, Naturvetenskapliga fakulteten, Matematikcentrum, Matematik LTH, Originator, Lund University, Faculty of Engineering, LTH, LTH Profile areas, LTH Profile Area: AI and Digitalization, Lunds universitet, Lunds Tekniska Högskola, LTH profilområden, LTH profilområde: AI och digitalisering, Originator

Πηγή: Proceedings of Machine Learning Research Bayesian optimization across the spectrum of knowledge. 235:20793-20817

Θεματικοί όροι: Natural Sciences, Computer and Information Sciences, Computer graphics and computer vision, Naturvetenskap, Data- och informationsvetenskap (Datateknik), Datorgrafik och datorseende, Mathematical Sciences, Computational Mathematics, Matematik, Beräkningsmatematik

Σύνδεσμος πρόσβασης: https://proceedings.mlr.press/v235/hussain24a.html

From Missing Pieces to Masterpieces: Image Completion With Context-Adaptive Diffusion

Συγγραφείς: Pourya Shamsolmoali, Masoumeh Zareapoor, Huiyu Zhou, Michael Felsberg, Dacheng Tao, Xuelong Li

Πηγή: IEEE Transactions on Pattern Analysis and Machine Intelligence. 47:6073-6087

Θεματικοί όροι: Computer graphics and computer vision, FOS: Computer and information sciences, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition, Diffusion models, Solid modeling, Training, Noise reduction, Adaptation models, Image reconstruction, Diffusion processes, Degradation, Coherence, Transformers, Image completion, diffusion models, context-adaptive discrepancy, Datorgrafik och datorseende

Περιγραφή αρχείου: application/pdf

Σύνδεσμος πρόσβασης: https://pubmed.ncbi.nlm.nih.gov/40184300
http://arxiv.org/abs/2504.14294
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-215351

Human bias and CNNs’ superior insights in satellite based poverty mapping

Συγγραφείς: Sarmadi, Hamid, Wahab, Ibrahim, Hall, Ola, Rögnvaldsson, Thorsteinn, Ohlsson, Mattias

Συνεισφορές: Lund University, Faculty of Social Sciences, Departments of Administrative, Economic and Social Sciences, Department of Human Geography, Lunds universitet, Samhällsvetenskapliga fakulteten, Samhällsvetenskapliga institutioner och centrumbildningar, Institutionen för kulturgeografi och ekonomisk geografi, Originator, Lund University, Faculty of Science, Centre for Environmental and Climate Science (CEC), Lunds universitet, Naturvetenskapliga fakulteten, Centrum för miljö- och klimatvetenskap (CEC), Originator, Lund University, Profile areas and other strong research environments, Strategic research areas (SRA), eSSENCE: The e-Science Collaboration, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Strategiska forskningsområden (SFO), eSSENCE: The e-Science Collaboration, Originator, Lund University, Profile areas and other strong research environments, Lund University Profile areas, LU Profile Area: Natural and Artificial Cognition, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Lunds universitets profilområden, LU profilområde: Naturlig och artificiell kognition, Originator

Πηγή: Scientific Reports. 14

Θεματικοί όροι: Social Sciences, Other Social Sciences, Samhällsvetenskap, Annan samhällsvetenskap, Natural Sciences, Computer and Information Sciences, Computer graphics and computer vision, Naturvetenskap, Data- och informationsvetenskap (Datateknik), Datorgrafik och datorseende

Σύνδεσμος πρόσβασης: https://doi.org/10.1038/s41598-024-74150-9

Parallel matters: Efficient polyp segmentation with parallel structured feature augmentation modules

Συγγραφείς: Guo, Qingqing, Fang, Xianyong, Wang, Kaibing, Shi, Yuqing, Wang, Linbo, Zhang, Enming, Liu, Zhengyi

Συνεισφορές: Lund University, Profile areas and other strong research environments, Lund University Profile areas, LU Profile Area: Light and Materials, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Lunds universitets profilområden, LU profilområde: Ljus och material, Originator, Lund University, Faculty of Engineering, LTH, LTH Profile areas, LTH Profile Area: Nanoscience and Semiconductor Technology, Lunds universitet, Lunds Tekniska Högskola, LTH profilområden, LTH profilområde: Nanovetenskap och halvledarteknologi, Originator, Lund University, Profile areas and other strong research environments, Strategic research areas (SRA), NanoLund: Centre for Nanoscience, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Strategiska forskningsområden (SFO), NanoLund: Centre for Nanoscience, Originator, Lund University, Faculty of Medicine, Department of Clinical Sciences, Malmö, Diabetes - Islet Patophysiology, Lunds universitet, Medicinska fakulteten, Institutionen för kliniska vetenskaper, Malmö, Diabetes - öpatofysiologi, Originator

Πηγή: IET Image Processing. 17(8):2503-2515

Θεματικοί όροι: Natural Sciences, Computer and Information Sciences, Computer graphics and computer vision, Naturvetenskap, Data- och informationsvetenskap (Datateknik), Datorgrafik och datorseende, Bioinformatics (Computational Biology), Bioinformatik (Beräkningsbiologi)

Σύνδεσμος πρόσβασης: https://doi.org/10.1049/ipr2.12813

Opportunities and challenges of on-board AI-based image recognition for small satellite Earth observation missions

Συγγραφείς: Bharadwaj Chintalapati, Arthur Precht, Sougata Hanra, Rene Laufer, Marcus Liwicki, Jens Eickhoff

Πηγή: Advances in Space Research. 75:6734-6751

Θεματικοί όροι: Computer graphics and computer vision, 0301 basic medicine, Earth observation, 0303 health sciences, Object detection, Deep learning, Signalbehandling, Datorgrafik och datorseende, On-board Artificial Intelligence, Small Satellite, 03 medical and health sciences, Signal Processing, Convolutional neural networks

Περιγραφή αρχείου: application/pdf

Σύνδεσμος πρόσβασης: http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-105174

The Birth of Computer Vision

Συγγραφείς: Högberg, Charlotte

Συνεισφορές: Lund University, Faculty of Engineering, LTH, Departments at LTH, Department of Technology and Society, Lunds universitet, Lunds Tekniska Högskola, Institutioner vid LTH, Institutionen för teknik och samhälle, Originator, Lund University, Faculty of Engineering, LTH, Departments at LTH, Department of Technology and Society, AI and Society, Lunds universitet, Lunds Tekniska Högskola, Institutioner vid LTH, Institutionen för teknik och samhälle, AI och samhälle, Originator

Πηγή: Tecnoscienza. 15(2):165-168

Θεματικοί όροι: Humanities and the Arts, History and Archaeology, Technology and Environmental History, Humaniora och konst, Historia och arkeologi, Teknik- och miljöhistoria, Social Sciences, Media and Communications, Samhällsvetenskap, Medie, kommunikations, och informationsvetenskaper, Natural Sciences, Computer and Information Sciences, Computer graphics and computer vision, Naturvetenskap, Data- och informationsvetenskap (Datateknik), Datorgrafik och datorseende

Περιγραφή αρχείου: electronic

Σύνδεσμος πρόσβασης: https://lucris.lub.lu.se/ws/files/207894041/TS30_BR_Ho_gberg.pdf

Integrating smooth motion assumptions with RANSAC-based sound source localization
Integration av antagande om mjuk rörelse i RANSAC-baserad lokalisering av ljudkälla

Συγγραφείς: Gulin, Jens, Åström, Kalle, Aminifar, Amir

Συνεισφορές: Lund University, Faculty of Engineering, LTH, Departments at LTH, Department of Electrical and Information Technology, Integrated Electronic Systems, Lunds universitet, Lunds Tekniska Högskola, Institutioner vid LTH, Institutionen för elektro- och informationsteknik, Integrerade elektroniksystem, Originator, Lund University, Faculty of Science, Centre for Mathematical Sciences, Mathematics (Faculty of Engineering), Computer Vision and Machine Learning, Lunds universitet, Naturvetenskapliga fakulteten, Matematikcentrum, Matematik LTH, Datorseende och maskininlärning, Originator, Lund University, Faculty of Engineering, LTH, LTH Profile areas, LTH Profile Area: AI and Digitalization, Lunds universitet, Lunds Tekniska Högskola, LTH profilområden, LTH profilområde: AI och digitalisering, Originator, Lund University, Faculty of Medicine, Department of Clinical Sciences, Lund, Section V, Diagnostic Radiology, (Lund), Stroke Imaging Research group, Lunds universitet, Medicinska fakulteten, Institutionen för kliniska vetenskaper, Lund, Sektion V, Diagnostisk radiologi, Lund, Stroke Imaging Research group, Originator, Lund University, Profile areas and other strong research environments, Strategic research areas (SRA), ELLIIT: the Linköping-Lund initiative on IT and mobile communication, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Strategiska forskningsområden (SFO), ELLIIT: the Linköping-Lund initiative on IT and mobile communication, Originator, Lund University, Profile areas and other strong research environments, Strategic research areas (SRA), eSSENCE: The e-Science Collaboration, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Strategiska forskningsområden (SFO), eSSENCE: The e-Science Collaboration, Originator, Lund University, Faculty of Science, Centre for Mathematical Sciences, Research groups at the Centre for Mathematical Sciences, Mathematical Imaging Group, Lunds universitet, Naturvetenskapliga fakulteten, Matematikcentrum, Forskargrupper vid Matematikcentrum, Mathematical Imaging Group, Originator, Lund University, Faculty of Engineering, LTH, Competence centers, LTH, NEXTG2COM – a Vinnova Competence Centre in Advanced Digitalisation, Lunds universitet, Lunds Tekniska Högskola, Kompetenscentrum, LTH, NEXTG2COM – ett Vinnova kompetenscenter inom Avancerad Digitalisering, Originator, Lund University, Faculty of Engineering, LTH, Departments at LTH, Department of Electrical and Information Technology, Secure and Networked Systems, Lunds universitet, Lunds Tekniska Högskola, Institutioner vid LTH, Institutionen för elektro- och informationsteknik, Säkerhets- och nätverkssystem, Originator

Πηγή: 33rd European Signal Processing Conference 33rd European Signal Processing Conference (EUSIPCO 2025).

Θεματικοί όροι: Engineering and Technology, Electrical Engineering, Electronic Engineering, Information Engineering, Signal Processing, Teknik, Elektroteknik och elektronik, Signalbehandling, Natural Sciences, Computer and Information Sciences, Computer graphics and computer vision, Naturvetenskap, Data- och informationsvetenskap (Datateknik), Datorgrafik och datorseende

Σύνδεσμος πρόσβασης: https://eusipco2025.org/wp-content/uploads/pdfs/0000226.pdf

Simultaneous multiple time scale imaging for kHz-MHz high-speed accelerometry

Συγγραφείς: Kornienko, Vassily, Andersson, David, Stiti, Mehdi, Ravelid, Jonas, Ek, Simon, Ehn, Andreas, Berrocal, Edouard, Kristensson, Elias

Συνεισφορές: Lund University, Faculty of Engineering, LTH, LTH Profile areas, LTH Profile Area: The Energy Transition, Lunds universitet, Lunds Tekniska Högskola, LTH profilområden, LTH profilområde: Energiomställningen, Originator, Lund University, Faculty of Science, Department of Physics, Combustion Physics, Lunds universitet, Naturvetenskapliga fakulteten, Fysiska institutionen, Förbränningsfysik, Originator, Lund University, Faculty of Engineering, LTH, LTH Profile areas, LTH Profile Area: Engineering Health, Lunds universitet, Lunds Tekniska Högskola, LTH profilområden, LTH profilområde: Teknik för hälsa, Originator, Lund University, Faculty of Engineering, LTH, LTH Profile areas, LTH Profile Area: Photon Science and Technology, Lunds universitet, Lunds Tekniska Högskola, LTH profilområden, LTH profilområde: Avancerade ljuskällor, Originator

Πηγή: Photonics Research Towards quantitative imaging using coded light Optical Multiplexing for Ultrafast Videography Strukturerad belysning för Ultrasnabb Videografi Structured Light for Ultrafast Videography. 10(7):1712-1722

Θεματικοί όροι: Natural Sciences, Computer and Information Sciences, Computer graphics and computer vision, Naturvetenskap, Data- och informationsvetenskap (Datateknik), Datorgrafik och datorseende

Σύνδεσμος πρόσβασης: https://doi.org/10.1364/PRJ.451108

Visualizing and Communicating Errors in Rendered Images

Συγγραφείς: Andersson, Pontus, Akenine-Möller, Tomas, Nilsson, Jim

Συνεισφορές: Lund University, Faculty of Science, Centre for Mathematical Sciences, Mathematics (Faculty of Engineering), Computer Vision and Machine Learning, Lunds universitet, Naturvetenskapliga fakulteten, Matematikcentrum, Matematik LTH, Datorseende och maskininlärning, Originator, Lund University, Faculty of Science, Centre for Mathematical Sciences, Mathematics (Faculty of Engineering), Lunds universitet, Naturvetenskapliga fakulteten, Matematikcentrum, Matematik LTH, Originator

Πηγή: Ray Tracing Gems II Evaluating and Improving Rendered Visual Experiences. :301-320

Θεματικοί όροι: Natural Sciences, Computer and Information Sciences, Computer graphics and computer vision, Naturvetenskap, Data- och informationsvetenskap (Datateknik), Datorgrafik och datorseende, Computer Sciences, Datavetenskap (Datalogi)

Σύνδεσμος πρόσβασης: https://link.springer.com/book/10.1007/978-1-4842-7185-8

Variable impedance skill learning for contact-rich manipulation

Συγγραφείς: Yang, Quantao, Dürr, Alexander, Topp, Elin Anna, Stork, Johannes, Stoyanov, Todor

Συνεισφορές: Lund University, Faculty of Engineering, LTH, Departments at LTH, Department of Computer Science, Robotics and Semantic Systems, Lunds universitet, Lunds Tekniska Högskola, Institutioner vid LTH, Institutionen för datavetenskap, Robotik och Semantiska System, Originator, Lund University, Faculty of Engineering, LTH, LTH Profile areas, LTH Profile Area: AI and Digitalization, Lunds universitet, Lunds Tekniska Högskola, LTH profilområden, LTH profilområde: AI och digitalisering, Originator, Lund University, Profile areas and other strong research environments, Strategic research areas (SRA), ELLIIT: the Linköping-Lund initiative on IT and mobile communication, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Strategiska forskningsområden (SFO), ELLIIT: the Linköping-Lund initiative on IT and mobile communication, Originator, Lund University, Faculty of Engineering, LTH, Departments at LTH, Department of Computer Science, Lunds universitet, Lunds Tekniska Högskola, Institutioner vid LTH, Institutionen för datavetenskap, Originator

Πηγή: IEEE Robotics and Automation Letters. 7(3):8391-8398

Θεματικοί όροι: Engineering and Technology, Electrical Engineering, Electronic Engineering, Information Engineering, Control Engineering, Teknik, Elektroteknik och elektronik, Reglerteknik, Robotics and automation, Robotik och automation, Natural Sciences, Computer and Information Sciences, Computer graphics and computer vision, Naturvetenskap, Data- och informationsvetenskap (Datateknik), Datorgrafik och datorseende

Σύνδεσμος πρόσβασης: https://doi.org/10.1109/LRA.2022.3187276

Reconstructing Three-Dimensional Models of Interacting Humans

Συγγραφείς: Fieraru, Mihai, Zanfir, Mihai, Oneata, Elisabeta, Popa, Alin Ionut, Olaru, Vlad, Sminchisescu, Cristian

Συνεισφορές: Lund University, Faculty of Science, Centre for Mathematical Sciences, Research groups at the Centre for Mathematical Sciences, Mathematical Imaging Group, Lunds universitet, Naturvetenskapliga fakulteten, Matematikcentrum, Forskargrupper vid Matematikcentrum, Mathematical Imaging Group, Originator, Lund University, Profile areas and other strong research environments, Strategic research areas (SRA), ELLIIT: the Linköping-Lund initiative on IT and mobile communication, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Strategiska forskningsområden (SFO), ELLIIT: the Linköping-Lund initiative on IT and mobile communication, Originator, Lund University, Profile areas and other strong research environments, Strategic research areas (SRA), eSSENCE: The e-Science Collaboration, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Strategiska forskningsområden (SFO), eSSENCE: The e-Science Collaboration, Originator, Lund University, Faculty of Engineering, LTH, LTH Profile areas, LTH Profile Area: AI and Digitalization, Lunds universitet, Lunds Tekniska Högskola, LTH profilområden, LTH profilområde: AI och digitalisering, Originator, Lund University, Profile areas and other strong research environments, Lund University Profile areas, LU Profile Area: Natural and Artificial Cognition, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Lunds universitets profilområden, LU profilområde: Naturlig och artificiell kognition, Originator, Lund University, Faculty of Science, Centre for Mathematical Sciences, Mathematics (Faculty of Engineering), Computer Vision and Machine Learning, Lunds universitet, Naturvetenskapliga fakulteten, Matematikcentrum, Matematik LTH, Datorseende och maskininlärning, Originator

Πηγή: IEEE Transactions on Pattern Analysis and Machine Intelligence. 47(12):10870-10881

Θεματικοί όροι: Natural Sciences, Computer and Information Sciences, Computer graphics and computer vision, Naturvetenskap, Data- och informationsvetenskap (Datateknik), Datorgrafik och datorseende

Estimates of Temporal Edge Detection Filters in Human Vision

Συγγραφείς: Ebelin, Pontus, Denes, Gyorgy, Akenine-Möller, Tomas, Åström, Kalle, Oskarsson, Magnus, McIlhagga, William H.

Συνεισφορές: Lund University, Faculty of Science, Centre for Mathematical Sciences, Mathematics (Faculty of Engineering), Computer Vision and Machine Learning, Lunds universitet, Naturvetenskapliga fakulteten, Matematikcentrum, Matematik LTH, Datorseende och maskininlärning, Originator, Lund University, Profile areas and other strong research environments, Lund University Profile areas, LU Profile Area: Light and Materials, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Lunds universitets profilområden, LU profilområde: Ljus och material, Originator, Lund University, Profile areas and other strong research environments, Lund University Profile areas, LU Profile Area: Natural and Artificial Cognition, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Lunds universitets profilområden, LU profilområde: Naturlig och artificiell kognition, Originator, Lund University, Faculty of Engineering, LTH, LTH Profile areas, LTH Profile Area: AI and Digitalization, Lunds universitet, Lunds Tekniska Högskola, LTH profilområden, LTH profilområde: AI och digitalisering, Originator, Lund University, Faculty of Engineering, LTH, LTH Profile areas, LTH Profile Area: Engineering Health, Lunds universitet, Lunds Tekniska Högskola, LTH profilområden, LTH profilområde: Teknik för hälsa, Originator, Lund University, Faculty of Medicine, Department of Clinical Sciences, Lund, Section V, Diagnostic Radiology, (Lund), Stroke Imaging Research group, Lunds universitet, Medicinska fakulteten, Institutionen för kliniska vetenskaper, Lund, Sektion V, Diagnostisk radiologi, Lund, Stroke Imaging Research group, Originator, Lund University, Profile areas and other strong research environments, Strategic research areas (SRA), ELLIIT: the Linköping-Lund initiative on IT and mobile communication, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Strategiska forskningsområden (SFO), ELLIIT: the Linköping-Lund initiative on IT and mobile communication, Originator, Lund University, Profile areas and other strong research environments, Strategic research areas (SRA), eSSENCE: The e-Science Collaboration, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Strategiska forskningsområden (SFO), eSSENCE: The e-Science Collaboration, Originator, Lund University, Faculty of Science, Centre for Mathematical Sciences, Research groups at the Centre for Mathematical Sciences, Mathematical Imaging Group, Lunds universitet, Naturvetenskapliga fakulteten, Matematikcentrum, Forskargrupper vid Matematikcentrum, Mathematical Imaging Group, Originator, Lund University, Faculty of Science, Centre for Mathematical Sciences, Mathematics (Faculty of Engineering), Lunds universitet, Naturvetenskapliga fakulteten, Matematikcentrum, Matematik LTH, Originator, Lund University, Faculty of Science, Centre for Mathematical Sciences, Lunds universitet, Naturvetenskapliga fakulteten, Matematikcentrum, Originator

Πηγή: ACM Transactions on Applied Perception Evaluating and Improving Rendered Visual Experiences. 21(2)

Θεματικοί όροι: Natural Sciences, Computer and Information Sciences, Computer graphics and computer vision, Naturvetenskap, Data- och informationsvetenskap (Datateknik), Datorgrafik och datorseende

Σύνδεσμος πρόσβασης: https://doi.org/10.1145/3639052