Tech Xplore

Interrupting encoder training in diffusion models enables more efficient generative AI

A new framework for generative diffusion models was developed by researchers at Science Tokyo, significantly improving ...
Gut

AI-empowered human microbiome research

Recent advances in high-throughput microbiome profiling have generated expansive data sets that offer unprecedented ...
IEEE

An Anomaly Detection Through Felis Territorial Search Optimized Continual Learning with Variational Auto-Encoder-Based Distributed Convolutional Neural Network (FeTSO-CnVDCN)

Abstract: The advancements in surveillance cameras and their widespread deployment have shifted the research toward autonomous detection of suspicious activities. Anomaly detection in real time is an ...
IEEE

LSTA-CNN: A Lightweight Spatiotemporal Attention-Based Convolutional Neural Network for ASD Diagnosis Using EEG

Abstract: Electroencephalography (EEG) is an effective assessment tool to identify autism spectrum disorders with low cost, and deep learning has been applied in EEG analysis for extracting meaningful ...
C&EN

Development of Coarse-Grained Lipid Force Fields Based on a Graph Neural Network

Department of Materials Science and Engineering, City University of Hong Kong, Kowloon 999077, Hong Kong China Department of Physics, City University of Hong Kong, Kowloon 999077, Hong Kong China ...
C&EN

GSH and Halides Directed Controllable Synthesis of Chiral Gold Nanostars for Sensitive Diagnosis of Nephritis Types Using SERS and Transformer Neural Network

Institute of Digitized Medicine and Intelligent Technology, Wenzhou Medical University, Wenzhou 325000, P. R. China ...