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. Agjelia Lydia C , Jenisha R, Dharshanashri G, Gokul K, Jayasuriya K , Poornesh M & Ragavendra R S


Plant leaf detection is a fundamental task in the field of agriculture and plant science. Accurate identification and classification of plant leaves can facilitate various applications such as disease detection, pest control, and crop yield prediction. This paper proposes a novel approach for plant leaf detection using deep learning techniques. The proposed method utilizes a convolutional neural network (CNN) to learn features from input images and classify them into different classes of plant leaves. We use transfer learning to fine-tune the pre-trained CNN on our dataset. The proposed approach is evaluated on a publicly available plant leaf dataset and achieves an accuracy of 95%. The results demonstrate that the proposed method is highly effective for plant leaf detection and classification. The approach can be applied to various real-world applications, including precision agriculture, plant breeding, and environmental monitoring.


Keywords — Plant leaves disease, Deep learning, CNN, Classification.

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