AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
TL;DR
Results demonstrate the proposed system’s ability to effectively detect early signs of coccidiosis in poultry droppings, enabling rapid intervention and potentially reducing economic losses associated with the disease.
This study applies transfer learning to two CNN architectures, MobileNetV2 and ResNet50, to classify red onion leaf diseases into three classes yellow spot, leaf curl, and healthy leaves, and shows that ResNet50 demonstrates better generalization, with a stable training curve, and outperforms MobileNetV2 in terms of ac...
The main objective of the proposed research is to design an enhanced deep learning-based poultry disease detection system that enables early and accurate classification of diseases, thereby reducing mortality rates, minimizing economic losses, and preventing the spread of infections.
: Poultry industry plays a vital role in the livestock industry. In poultry production, disease breakouts can cause a fall in production performance and, at times, can cause significant mortality which could result in tremendous economic loss. To realize the low-cost, contactless poultry health status detection for lar...
Fish disease poses a substantial threat to the productivity and sustainability of Indian major carps (IMCs) in aquaculture. Early and accurate fish disease detection is crucial to minimizing economic losses and ensuring fish health management. In this study, we developed a lightweight deep learning model, FishMoViT...
Parasitic infection is one of the common health problems of livestock in Bangladesh. Due to the country’s climate, heavy monsoon rainfall, low biosecurity in farms, and high humidity, along with the presence of suitable vector organisms, gastrointestinal parasitism remains widespread in cattle and other livestock. The...
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