Enhancing Plant Leaf Classification with Deep Learning: Automating Feature Extraction for Accurate Species Identification
DOI:
https://doi.org/10.56294/piii2025513Keywords:
Plant leaf classification, Deep learning, Evaluation metrics, CNN, Data augmentation, Optimizers, ANN, Regularization, VGG, RNN, LSTM, AutoencodersAbstract
Plant leaf classification using deep learning provides an automated approach that surpasses traditional methods reliant on manual feature selection. Convolutional Neural Networks (CNNs) excel at learning intricate patterns from leaf images, extracting valuable features that contribute to accurate plant species identification. These models enhance classification precision by automating feature extraction, thereby improving efficiency and reliability. By leveraging deep learning, plant recognition systems can become more dependable, and their classification accuracy is significantly increased, minimizing human error and manual intervention.
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Copyright (c) 2025 Chilukuri Ganesh, Gandikota Harshavardhan, Naishadham Radha Sri Keerthi, Raj Veer Yabaji, Rajveer Yabaji Meghana Sadhu (Author)
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