DEEP LEARNING-BASED PLANT IDENTIFICATION AND CLASSIFICATION USING CONVOLUTIONAL NEURAL NETWORKS

Dr. V. VAIDEHI, Dr. VIJI VINOD

Manuscript Title:

DEEP LEARNING-BASED PLANT IDENTIFICATION AND CLASSIFICATION USING CONVOLUTIONAL NEURAL NETWORKS

Author:

Dr. V. VAIDEHI, Dr. VIJI VINOD

DOI Number:

DOI:10.5281/zenodo.10683576

Published : 2024-02-10

About the author(s)

1. Dr. V. VAIDEHI - Assistant Professor, Faculty of Computer Applications, Dr. M.G.R. Educational and Research Institute, Chennai.
2. Dr. VIJI VINOD - Professor, Faculty of Computer Applications, Dr. M.G.R. Educational and Research Institute, Chennai.

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Abstract

The collection is composed of six common medicinal plants found throughout Tamil Nadu. Sophisticated and tuned CNN (Convolutional Neural Network) model is used for core classification. 70% of dataset can be used for training the model. 30% of dataset used for validation. Randomization and augmentation of dataset can be done before feeding to model. ECOC framework is used. One-versus-all coding design is used with SVM classifier. CNN models are used for feature extraction used as input for model.

Keywords

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