Results 221 to 230 of about 64,505 (309)
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley +1 more source
ThermVision-DB: A synthetic LWIR thermal face dataset for privacy-preserving thermal vision research. [PDF]
Farooq MA, Shariff W, Corcoran P.
europepmc +1 more source
Federated Learning for Privacy-Preserving Cybersecurity: A Review on Secure Threat Detection
Nirav Kumar Prajapati
openalex +1 more source
Hermes: A Privacy-Preserving Approximate Search Framework for Big Data
Zhigang Zhou +3 more
openalex +1 more source
Large language models are transforming microbiome research by enabling advanced sequence profiling, functional prediction, and association mining across complex datasets. They automate microbial classification and disease‐state recognition, improving cross‐study integration and clinical diagnostics.
Jieqi Xing +4 more
wiley +1 more source
FedSCOPE: Federated cross-domain sequential recommendation with decoupled contrastive learning and privacy-preserving semantic enhancement. [PDF]
Zhao L +6 more
europepmc +1 more source
Privacy-Preserving Synthetic Continual Semantic Segmentation for Robotic Surgery
Mengya Xu +3 more
openalex +1 more source
Flexible Memory: Progress, Challenges, and Opportunities
Flexible memory technology is crucial for flexible electronics integration. This review covers its historical evolution, evaluates rigid systems, proposes a flexible memory framework based on multiple mechanisms, stresses material design's role, presents a coupling model for performance optimization, and points out future directions.
Ruizhi Yuan +5 more
wiley +1 more source
Privacy-preserving federated credit risk models: evaluating differential privacy and homomorphic encryption techniques. [PDF]
Naresh VS, Ayyappa D.
europepmc +1 more source
Exosomes are emerging as powerful biomarkers for disease diagnosis and monitoring. This review highlights the integration of surface‐enhanced Raman spectroscopy with artificial intelligence to enhance molecular fingerprinting of exosomes. Machine learning and deep learning techniques improve spectral interpretation, enabling accurate classification of ...
Munevver Akdeniz +2 more
wiley +1 more source

