Results 281 to 290 of about 1,718,101 (355)

Experimental Demonstration of Temporally Aware Fault‐Tolerant Sensor Fusion Using Memristive Associative Learning

Advanced Electronic Materials, EarlyView.
In dynamic driving scenarios, the proposed approach ensures only temporally aligned sensor inputs to make driving decisions, preventing false activations. By enabling selective hardware‐level learning, it achieves fast, reliable responses under noisy conditions.
Kapil Bhardwaj, Ashfak Nehal, Dmitrii Semenov, Roman Sotner, Sayani Majumdar   +4 more
wiley   +1 more source

Nondestructive sheet resistance prediction of silver nanowire transparent electrode with convolutional neural network. [PDF]

Sci Rep
Han Y, Ndikumana J, Choi S, Lim D, Kim I, Kim JY, Rho J, An K.   +7 more
europepmc   +1 more source

Chronic Disease Monitoring Using Advanced Compliant Materials for Bioelectronics

Advanced Electronic Materials, EarlyView.
Compliant bioelectronic systems enable continuous monitoring of chronic disease through soft, stretchable materials and tissue‐conformal designs that support stable electrophysiological, mechanical, and biochemical sensing. Integration of diverse sensing modalities with thoughtful material selection, device architectures, and advanced fabrication ...
Han Kim, Mabel Bartlett, Liyang Wang, Karl Bates, Mengdi He, Myungbo Kim, Carmel Majidi, Tzahi Cohen‐Karni   +7 more
wiley   +1 more source

Effective deep convolutional neural network with attention mechanism for Alzheimer disease classification. [PDF]

Front Radiol
Lakshmanan SK, Muthusamy M, Dhanaraj RK, Sureshkumar A, Sayeed MS, Mohamed MYN, Rathinam G.   +6 more
europepmc   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

A generative explainable model for antimicrobial peptide prediction using bidirectional temporal convolutional neural network. [PDF]

Sci Rep
Ali F, Khalid M, Alsini R, Yafoz A, Alkhalifah T, Du MZ.   +5 more
europepmc   +1 more source

SigmaFormer: Augmenting transformer encoders with COSMO sigma profiles for pure component property prediction

AIChE Journal, EarlyView.
Abstract Transformer‐based molecular models pretrained on SMILES strings demonstrate strong performance in property prediction. However, these model often lack explicit integration of molecular surface charge distributions that govern intermolecular interactions such as hydrogen bonding and polarity.
Tae Hyun Kim, Silabrata Pahari, Joseph Sang‐Il Kwon   +2 more
wiley   +1 more source

ICU-EEG Pattern Detection by a Convolutional Neural Network. [PDF]

Ann Clin Transl Neurol
Degano G, Quintard H, Kleinschmidt A, Francini N, Sarbu OE, De Stefano P.   +5 more
europepmc   +1 more source

Harnessing Large Language Models to Advance Microbiome Research: From Sequence Analysis to Clinical Applications

Advanced Intelligent Discovery, EarlyView.
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, He Wang, Yangyang Sun, Xiaoquan Su, Shunyao Wu   +4 more
wiley   +1 more source