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ISSN 1004-9037
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Edited by: Editorial Board of Journal of Data Acquisition and Processing
P.O. Box 2704, Beijing 100190, P.R. China
Sponsored by: Institute of Computing Technology, CAS & China Computer Federation
Undertaken by: Institute of Computing Technology, CAS
Published by: SCIENCE PRESS, BEIJING, CHINA
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      1 Jan 2024, Volume 39 Issue 1   
    Article

    PLANT IDENTIFICATION AND CLASSIFICATION THROUGH CONVOLUTIONAL NEURAL NETWORKS: A DEEP LEARNING APPROACH
    Dr.V.Vaidehi1, Dr. Raynukaazhakarsamy2
    Journal of Data Acquisition and Processing, 2024, 39 (1): 1291-1297 . 

    Abstract

    Six commonly found native medicinal herbs from Tamil Nadu make up the dataset. For primary classification tasks, a powerful CNN (Convolutional Neural Network) model is used. Thirty percent of the dataset is set aside for validation and the remaining seventy percent is used to train the model. Techniques for dataset augmentation and randomization are used before model input. Using SVM (Support Vector Machine) classifiers in conjunction with a one-versus-all coding architecture, the ECOC (Error Correcting Output Codes) framework is put into practice. CNN models are used to extract features, which are then fed into the classification model.

    Keyword

    CNN, SVM, Deep Learning, ANN (Artificial Neural Network), Classification, Performance Evaluation


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ISSN 1004-9037

         

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