Researchers developed a deep learning pipeline integrating semantic segmentation, regression-based severity estimation, and disease classification for quantifying stress severity in field crops. The s…
Researchers developed a hybrid machine learning approach combining EfficientNetB0 feature extraction with Random Forest classification to achieve 94.58% accuracy and sub-millisecond inference for real…
Researchers evaluated six deep learning architectures for maritime object detection, including CNNs and a Vision Transformer (ViT), using a dataset of 6,468 images under various weather conditions. Th…
A developer built LifeLine Loop, an AI-powered food redistribution platform that connects food donors with NGOs. The system uses computer vision to classify food from photos, estimates servings, and p…
Researchers have developed WISE-HAR, an ensemble deep learning framework that uses WiFi signals to recognize human activities including walking and arm-waving with 94.87% accuracy. The framework, test…
Researchers at the University of Cambridge have developed the first large-scale Ukrainian handwritten text generation system, creating a dataset of 126,177 images from 308 writers and retraining a dif…