Tag: Computer Vision

Researchers have unveiled a generative adversarial network that rebuilds faces obscured by up to 70 percent occlusion while preserving the ...

A deep learning pipeline combining YOLOv5 detection, skeleton extraction and neural network classification can recognize falls, collisions and shelf climbing ...

Researchers have developed CHS-Net, a hybrid deep learning architecture that sets a new benchmark for segmenting cracks, erosion, and delamination ...

A new RGB-D perception-to-action framework called E-YOLOv11-RGBD raised robotic greenhouse harvesting success from 51.7 to 92.5 percent by converting AI ...

Researchers in India have built a hybrid graph neural network framework that converts retinal images into graph structures, achieving up ...

A hierarchical computer vision framework combining object detection, SAM2 segmentation, and multi-object tracking enables contactless, individual-level dairy cow behavior monitoring ...

Researchers in Algeria have combined convolutional neural networks with a Swin Transformer to detect network intrusions with up to 99.69 ...

Researchers in China have developed a lightweight transformer model with a novel cross-axis attention module and a feature memory component ...

Researchers have developed a trajectory-free, semi-supervised anomaly detection framework that monitors entire hen flocks through statistical activity and density cues, ...

Researchers have developed a dual-stream convolutional neural network that fuses RGB imagery with vectorized Error Level Analysis and CBAM attention ...

Researchers in Türkiye combined transfer learning with MobileNetV2, Xception, and classical classifiers to classify five rice varieties with up to ...

Researchers have released AquaCal, an open-source Python library that corrects the depth-dependent errors caused by light refraction in multi-camera calibration ...

A new computational framework called STARIT converts the spatial positions of mRNA molecules inside cells into image tensors, allowing deep ...

Researchers have built InterPet4D, the first large-scale multimodal 4D dataset of human–dog interactions, and used it to train an AI ...

Researchers have built an AI framework that combines live video of floc formation, real-time turbidity sensing and physics-based equations to ...

Researchers in Vietnam have developed WGPose-LL, a deep learning method that uses paired well-lit images to guide human pose estimation ...

Researchers at Shiv Nadar University have developed a dual-path AI framework that combines a residual gated autoencoder with patchwise nearest-neighbor ...

Researchers have developed a lightweight frequency-based AI detector that achieves state-of-the-art accuracy and real-time speed on cluttered traffic scenes, running ...

A new lightweight deep learning framework called LCASP-MMANet achieves state-of-the-art sign language recognition accuracy while remaining efficient enough for real-world, ...

Researchers used a consumer tablet app to capture facial blendshape features that objectively quantify Parkinson's hypomimia, revealing asymmetry and interaction ...