Application of Deep Neural Networks for Automatic Irony Detection in Russian-Language Texts

Authors: Kosterin, M. A.^{Aff1, IDS0146411624700469_cor1}, Paramonov, I. V.^{Aff1, IDS0146411624700469_cor2}

Source: Automatic Control and Computer Sciences. 58(7):1073-1081

Application of deep neural networks for automatic irony detection in Russian texts

Authors: Maksim A. Kosterin, Ilya V. Paramonov

Source: Моделирование и анализ информационных систем, Vol 31, Iss 1, Pp 90-101 (2024)

Subject Terms: neural network-based classifier, 05 social sciences, 0202 electrical engineering, electronic engineering, information engineering, irony detection, deep learning, Information technology, 02 engineering and technology, natural language processing, 0509 other social sciences, T58.5-58.64, sarcasm detection, bert

Access URL: https://doaj.org/article/f377da69d72541bba106b0503ce683f2

Dynamic Atlas-Based Segmentation and Quantification of Neuromelanin-Rich Brainstem Structures in Parkinson Disease

Authors: Ariz, M., Abad, R.C., Castellanos, G., Martinez, M., Munoz-Barrutia, A., Fernandez-Seara, M.A., Pastor, P., Pastor, M.A., Ortiz-de-Solorzano, C.

Source: IEEE Transactions on Medical Imaging IEEE Trans. Med. Imaging Medical Imaging, IEEE Transactions on. 38(3):813-823 Mar, 2019

Gabor filter based image representation for object classification

Authors: Rizvi, Syed Tahir Hussain, Cabodi, Gianpiero, Gusmao, Pedro, Francini, Gianluca

Source: 2016 International Conference on Control, Decision and Information Technologies (CoDIT) Control, Decision and Information Technologies (CoDIT), 2016 International Conference on. :628-632 Apr, 2016

Relation: 2016 International Conference on Control, Decision and Information Technologies (CoDIT)

Neural Network-Based Sentiment Classification of Russian Sentences into Four Classes

Authors: Maksim A. Kosterin, Ilya V. Paramonov

Source: Моделирование и анализ информационных систем, Vol 29, Iss 2, Pp 116-133 (2022)

Subject Terms: neural network-based classifier, sentiment analysis, 0202 electrical engineering, electronic engineering, information engineering, Information technology, 02 engineering and technology, natural language processing, T58.5-58.64, bert

Access URL: https://doaj.org/article/ebd11ef06e8443c093063e2a7d8e2773

An Approach to Find Proper Execution Parameters of n-Gram Encoding Method Based on Protein Sequence Classification

Authors: Saha, Suprativ^Aff13, Bhattacharya, Tanmay^Aff14

Contributors: Barbosa, Simone Diniz Junqueira, Editorial Board Member^Aff1, Filipe, Joaquim, Editorial Board Member^Aff2, Ghosh, Ashish, Editorial Board Member^Aff3, Kotenko, Igor, Editorial Board Member^Aff4, Yuan, Junsong, Editorial Board Member^Aff5, Zhou, Lizhu, Editorial Board Member^Aff6, Singh, Mayank, editor^Aff7, Gupta, P.K., editor^Aff8, Tyagi, Vipin, editor^Aff9, Flusser, Jan, editor^Aff10, Ören, Tuncer, editor^Aff11, Kashyap, Rekha, editor^Aff12

Source: Advances in Computing and Data Sciences : Third International Conference, ICACDS 2019, Ghaziabad, India, April 12–13, 2019, Revised Selected Papers, Part II. 1046:294-303