A developer built Nose ID, a biometric system that identifies dogs by their unique nose-prints using a pretrained MobileNetV2 as a feature extractor and cosine similarity for matching. The system also…
IREE, an open-source compiler from the IREE project, now compiles machine learning models to native RISC-V CPU code with support for the RISC-V Vector extension (RVV), hand-written microkernels, and d…
Perforated AI released a perforated version of ResNet-18 on Hugging Face that matches ResNet-34's performance while maintaining ResNet-18's smaller size and compute efficiency, using dendritic optimiz…
A study using EEG signals and a custom convolutional neural network (CNN) predicted the outcome of repetitive transcranial magnetic stimulation (rTMS) therapy for major depressive disorder (MDD) with …
ForensicNet, a lightweight deep learning framework combining MobileNetV2 with Convolutional Block Attention Modules, achieves 92.4% accuracy and 90.8% precision on face identification across 15,000 im…
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…