Abstract: Plant leaf diseases pose a major challenge in the agricultural field, leading to poor crop performance and impacting food safety. Timely identification and accurate classification of ...
Abstract: In this work designs and implements an intelligent AI-powered plant disease detection and classification system through Convolutional Neural Network. This study builds on a key limitation in ...
Abstract: Agricultural productivity is helpless against various diseases that result in significant losses in terms of resources. These losses rise rapidly in isolated locations with limited resources ...
1 College of Agronomy, Sichuan Agricultural University, Chengdu, China 2 Yibin Municipal Company of Sichuan Provincial Tobacco Corporation, Yibin, China Tobacco leaf diseases significantly affect ...
Introduction: Jackfruit cultivation is highly affected by leaf diseases that reduce yield, fruit quality, and farmer income. Early diagnosis remains challenging due to the limitations of manual ...
A Flask backend for plant disease detection using pre-trained Keras models (best_custom_cnn_model.h5, plant_disease_resnet50_model.h5) with an image preprocessing pipeline (preprocess.py) and app.py ...
Abstract: This study introduces an exhaustive classification system for the detection of rutabaga plant diseases is presented in this research. Clubroot, Powdery Mildew, Downy Mildew, ...
Abstract: With the use of a combination of cutting-edge deep learning techniques, such as artificial neural networks, convolutional neural networks, and support vector machines, a unique method for ...
The PlantIF framework consists of image and text feature extractors, semantic space encoders, and a multimodal feature fusion module. Image and text feature extractors are used to present visual and ...