A team of researchers at Rice University and Baylor College of Medicine has developed a new strategy for identifying ...

Alessandro Ingrosso, researcher at the Donders Institute for Neuroscience, has developed a new mathematical method in ...

Our brain is a complex organ. Billions of nerve cells are wired in an intricate network, constantly processing signals, enabling us to recall memories or to move our bodies.

Researchers from the USC Viterbi School of Engineering are presenting 24 papers at the 2025 International Conference on Learning Representations (ICLR), Apr. 24-28, one of the premier global ...

Add a description, image, and links to the deep-learning-object-detection topic page so that developers can more easily learn about it.

This repository offers a comprehensive collection of tutorials on state-of-the-art computer vision models and techniques. Explore everything from foundational architectures like ResNet to cutting-edge ...

In handheld mode, quality mode will still output a 1080p image with DLSS and dynamic resolution scaling, targeting 30fps, while performance mode will see a drop in resolution to 720p, "with the ...

Modern traffic monitoring systems typically rely on AI-based object detection and tracking models ... targets specific areas of the frame where vehicles are detected, sampling these regions for ...

Abstract: Existing unsupervised salient object detection (USOD) methods usually rely on low-level saliency ... and extract high-level saliency from natural images through a contrastive learning ...