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Developing A Neural Network-Based Model for Identifying Medicinal Plant Leaves Using Image Recognition Techniques.

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Title: Developing A Neural Network-Based Model for Identifying Medicinal Plant Leaves Using Image Recognition Techniques.
Authors: Tiwari, Nidhi, Gupta, Bineet Kumar, Prakash, Abhijityaditya, Tiwari, Kartikesh, Alshmrany, Sami, Ali, Arshad, Husain, Mohammad, Singh, Devendra
Source: Journal of Advanced Zoology; 2023 Supplement, Vol. 44, p1944-1958, 15p
Subject Terms: Image recognition (Computer vision), Pattern recognition systems, Artificial neural networks, Digital image processing, Neural computers, Plant identification, Medical marijuana, Medicinal plants
Abstract: Herbal plants contribute an important role in people's health and the environment, as they can provide both medical benefits and oxygen. Many herbal plants contain valuable therapeutic elements that can be passed down to future generations. Traditional methods of identifying plant species, such as manual measurement and examination of characteristics, are labor-intensive and time-consuming. To address this, there has been a push to develop more efficient methods using technology, such as digital image processing and pattern recognition techniques. The exact recognition of plants uses methodologies like computer vision and neural networks, which have been proposed earlier. This approach involves neural network models such as CNN, ALexnet, and ResNet for identifying the medical plants based on their respective features. Classification metrics give the 96.82 average accuracies. These results have been promising, and further research will involve using a larger dataset and going more into deep-learning neural networks to improve the accuracy of medicinal plant identification. It is hoped that a web or mobile-based system for automatic plant identification can help increase knowledge about medicinal plants, improve techniques for species recognition, and participate in the preservation of species that are considered ad endangered. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Advanced Zoology is the property of Journal of Advanced Zoology and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Complementary Index
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  Data: Developing A Neural Network-Based Model for Identifying Medicinal Plant Leaves Using Image Recognition Techniques.
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  Data: Journal of Advanced Zoology; 2023 Supplement, Vol. 44, p1944-1958, 15p
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  Data: <searchLink fieldCode="DE" term="%22Image+recognition+%28Computer+vision%29%22">Image recognition (Computer vision)</searchLink><br /><searchLink fieldCode="DE" term="%22Pattern+recognition+systems%22">Pattern recognition systems</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+neural+networks%22">Artificial neural networks</searchLink><br /><searchLink fieldCode="DE" term="%22Digital+image+processing%22">Digital image processing</searchLink><br /><searchLink fieldCode="DE" term="%22Neural+computers%22">Neural computers</searchLink><br /><searchLink fieldCode="DE" term="%22Plant+identification%22">Plant identification</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+marijuana%22">Medical marijuana</searchLink><br /><searchLink fieldCode="DE" term="%22Medicinal+plants%22">Medicinal plants</searchLink>
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  Data: Herbal plants contribute an important role in people's health and the environment, as they can provide both medical benefits and oxygen. Many herbal plants contain valuable therapeutic elements that can be passed down to future generations. Traditional methods of identifying plant species, such as manual measurement and examination of characteristics, are labor-intensive and time-consuming. To address this, there has been a push to develop more efficient methods using technology, such as digital image processing and pattern recognition techniques. The exact recognition of plants uses methodologies like computer vision and neural networks, which have been proposed earlier. This approach involves neural network models such as CNN, ALexnet, and ResNet for identifying the medical plants based on their respective features. Classification metrics give the 96.82 average accuracies. These results have been promising, and further research will involve using a larger dataset and going more into deep-learning neural networks to improve the accuracy of medicinal plant identification. It is hoped that a web or mobile-based system for automatic plant identification can help increase knowledge about medicinal plants, improve techniques for species recognition, and participate in the preservation of species that are considered ad endangered. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Advanced Zoology is the property of Journal of Advanced Zoology and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.17762/jaz.v44is-5.1564
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        Text: English
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        PageCount: 15
        StartPage: 1944
    Subjects:
      – SubjectFull: Image recognition (Computer vision)
        Type: general
      – SubjectFull: Pattern recognition systems
        Type: general
      – SubjectFull: Artificial neural networks
        Type: general
      – SubjectFull: Digital image processing
        Type: general
      – SubjectFull: Neural computers
        Type: general
      – SubjectFull: Plant identification
        Type: general
      – SubjectFull: Medical marijuana
        Type: general
      – SubjectFull: Medicinal plants
        Type: general
    Titles:
      – TitleFull: Developing A Neural Network-Based Model for Identifying Medicinal Plant Leaves Using Image Recognition Techniques.
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              M: 09
              Text: 2023 Supplement
              Type: published
              Y: 2023
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