Results 91 to 100 of about 11,006,319 (257)

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source

Temporal and spatial self supervised learning methods for electrocardiograms

Scientific Reports
The limited availability of labeled ECG data restricts the application of supervised deep learning methods in ECG detection. Although existing self-supervised learning approaches have been applied to ECG analysis, they are predominantly image-based ...
Wenping Chen, Huibin Wang, Lili Zhang, Min Zhang   +3 more
doaj   +1 more source

Audio-Based Emotion Recognition Using Self-Supervised Learning on an Engineered Feature Space

AI
Emotion recognition models using audio input data can enable the development of interactive systems with applications in mental healthcare, marketing, gaming, and social media analysis.
Peranut Nimitsurachat, Peter Washington
doaj   +1 more source

Radiative Thermal Management for Extreme Environments: Mechanisms and Design Strategies

Advanced Materials, EarlyView.
In this review, we discuss the fundamental mechanisms of radiative cooling and solar heating, material and structural design strategies, hybrid approaches integrating additional heat transfer pathways, and durability‐oriented designs addressing environmental stresses.
Hyung Rae Kim, Haeseong Kim, Joo Hwan Ko, Gil Ju Lee, Dae‐Hyeong Kim, Young Min Song   +5 more
wiley   +1 more source

Tamper‐Responsive Physical Unclonable Functions via Graphene‐Interlayered Block Copolymer Random Structures

Advanced Materials, EarlyView.
Self‐invalidating multilayer physical unclonable functions (PUFs) integrate fingerprint‐like metal nanopattern bilayers from block copolymer templates with highly reactive reduced graphene oxide (rGO) interlayers. This tamper‐responsive architecture blocks all unauthorized physical and chemical replication attempts while autonomously deactivating ...
Gyu Hui Jo, Dae Hui Park, Jeong‐Ho Jang, Woo Seok Tack, Jin Man Kim, Hak Ki Yu, Hyeong Min Jin, Jang Hwan Kim   +7 more
wiley   +1 more source

Advances in Bio‐Integrated Edge Computing Systems for Smart and Connected Health

Advanced Materials, EarlyView.
This review explores advances in bio‐integrated edge computing for healthcare, focusing on co‐designing computing, sensing, and energy strategies to overcome integration and power challenges for optimized, decentralized operation. ABSTRACT Recent advances in bio‐integrated healthcare technologies have enabled continuous, high‐resolution monitoring and ...
Gyuwon Kim, Seungwon Yoo, Tae Woog Kang, Yunuo Huang, Woon‐Hong Yeo   +4 more
wiley   +1 more source

Self-Supervised Attentive Feature Learning for Alzheimer’s Disease Detection

International Journal of Interactive Multimedia and Artificial Intelligence
Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that leads to memory loss and a decline in cognitive abilities. It primarily affects older adults and is the most common cause of dementia.
Hela Elmannai, Nasir Saleem, Sami Bourouis, Reem Ibrahim Alkanhel   +3 more
doaj   +1 more source

A Simple Descriptor for Solid‐State Ionic Conductors Across Chemistries

Advanced Materials, EarlyView.
Researchers develop a simple and transferable descriptor, distance contraction, for solid‐state ion migration across Li‐, Na‐, K‐, and Mg‐ion conductors and diverse anion chemistries. By capturing the maximum local contraction experienced by the migrating ion, the descriptor enables rapid materials screening and unifies diverse ion‐transport mechanisms.
Ramanuja Srinivasan Saravanan, Charles E. Schwarz, Felix Adams, Kiyan Amirian, Yifei Mo   +4 more
wiley   +1 more source

A semi-supervised spam mail detector [PDF]

, 2006
This document describes a novel semi-supervised approach to spam classification, which was successful at the ECML/PKDD 2006 spam classification challenge.
Pfahringer, Bernhard
core  

Federated Self-supervised Learning for Heterogeneous Clients

, 2022
Federated Learning has become an important learning paradigm due to its privacy and computational benefits. As the field advances, two key challenges that still remain to be addressed are: (1) system heterogeneity - variability in the compute and/or data
Ghosh, Joydeep, Makhija, Disha, Ho, Nhat
core