CES 2026 showcases the latest AI-powered devices and systems, from vision chips for automotive to sensing solutions for AI ...

A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic sequences. By automating feature extraction and capturing long ...

With PFITRE, Brookhaven scientists achieve breakthrough 3D imaging in nanoscale X-ray tomography, combining AI and physics for superior clarity and precision.

Abstract: In image segmentation by deep learning, encoder-decoder Convolutional Neural Network (CNN) architectures are fundamental for creating and learning representations. However, with many filters ...

Abstract: This study investigates the application of Spiking Neural Network (SNN) in seismic signal denoising by developing a Convolutional Neural Network (CNN) to SNN conversion framework. We focus ...

1 College of Electronic Science and Technology, National University of Defense Technology, Changsha, China 2 College of Electronics and Internet of Things, Chongqing Polytechnic University of ...

School of Electronics Engineering (SENSE), Vellore Institute of Technology, Chennai, India Introduction: In recent years, Deep Learning (DL) architectures such as Convolutional Neural Network (CNN) ...

Researchers in China have created a dataset of various PV faults and normalized it to accommodate different array sizes and typologies. After testing the new approach in combination with the 1D-CNN ...

Aptos’ native token has surged 12% after the launch of Shelby in partnership with Jump Crypto. Shelby is a storage network designed to offer fast, decentralized storage for Web3 and AI. Key metrics ...

Background: Early detection is clinically crucial for the strategic handling of sarcopenia, yet the screening process, which includes assessments of muscle mass, strength, and function, remains ...