AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
TL;DR
The results show that the proposed SSO-DANet framework is an accurate, stable, and resource-efficient method for intelligent potato disease diagnosis and precision agriculture applications.
Rice leaf diseases have a great impact on the productivity and food security of crops. Thus, there is a necessity for development of accurate and fast automatic rice leaf disease detection. In the current paper, we propose an optimized deep learning model for multi-class rice leaf disease detection through transfer lea...
A comprehensive and systematic review of state-of-the-art methods for detecting potato leaf disease, covering convolutional neural networks, transformer-based architectures, and hybrid models, and a strategic comparative analysis is conducted.
Potato diseases pose a serious threat to the productivity and quality of potato crops; the most important ones are early blight and late blight, which require fast and accurate automated detection. This study introduces DeepCropGuard, a combined DenseNet–Vision Transformer network to classify potato diseases and suppor...
This study improves potato leaf disease detection using a fine-tuned InceptionV3 with data augmentation and dropout, while Grad-CAM visualizations enhance model interpretability, reliability, and practical utility for accurate agricultural disease diagnosis.
Potato (Solanum tuberosum) is a globally important food crop whose yield losses, caused by foliar diseases including early blight, late blight, and a range of bacterial, fungal, viral, nematode, and pest-induced conditions, are often difficult to identify in the field and costly to diagnose. This paper introduces a pot...
Potato cultivation is crucial to global agriculture, but continues to face challenges from various disturbances, including six classes of potato diseases: pests, nematodes, viruses, fungi, Phytophthora, and bacteria. These diseases can spread rapidly across fields, causing potato shortages, resulting in significant los...
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