Results 151 to 160 of about 32,689 (273)

A Siamese Network-Based Method for Improving the Performance of Sleep Staging with Single-Channel EEG. [PDF]

Biomedicines, 2023
You Y, Guo X, Yang Z, Shan W.
europepmc   +1 more source

Thermochromic Radiative Cooling Coatings with Robust Superhydrophobicity for Energy‐Efficient Buildings

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
A scalable, color‐adaptive radiative cooling coating is developed to enable dynamic spectral regulation via a reversible thermochromic transition at ~45 °C and a high solar reflectance of 91.7%. The coating achieves 4.44 °C outdoor sub‐ambient cooling while providing robust superhydrophobicity and environmental durability through its micro/nano ...
Ziqi Li, Akbar Bashir, Chak‐Yin Tang, Gary Chi‐Pong Tsui, Yan Chen, Jie Cui, Xing Ouyang, Chen Liu, Dazhu Chen   +8 more
wiley   +1 more source

A deep Siamese network framework for precision phage selection in pulmonary infections. [PDF]

Front Med (Lausanne)
Wang X, Fu M, Lin S, Wang Y, Pei H.
europepmc   +1 more source

Kinship identification using age transformation and Siamese network. [PDF]

PeerJ Comput Sci, 2022
Abbas A, Shoaib M.
europepmc   +1 more source

Cardiorespiratory cross‐frequency coupling biomarker for sudden unexpected death in epilepsy

Epilepsia, EarlyView.
Abstract Objective Sudden unexpected death in epilepsy (SUDEP) often follows generalized tonic–clonic seizures during sleep, likely resulting from impaired brainstem cardiorespiratory function. We used ictal electrocardiogram (ECG)‐based cross‐frequency phase–amplitude coupling (PAC) to detect cardiorespiratory disruptions, comparing SUDEP to non‐SUDEP
Adam C. Gravitis, Richard Wennberg, Peter L. Carlen, Yotin Chinvarun, Victor Lira, Juliana Laze, Orrin Devinsky, Berj L. Bardakjian   +7 more
wiley   +1 more source

Enhanced cattle identification using Siamese network and MobileViT with EMA attention. [PDF]

Front Vet Sci
Han M, Li B, Li Q, Wang Y, Yang M, Gao C.   +5 more
europepmc   +1 more source

Improving ΔΔG Predictions with a Multitask Convolutional Siamese Network. [PDF]

J Chem Inf Model, 2022
McNutt AT, Koes DR.
europepmc   +1 more source

Siamese networks for generating adversarial examples

, 2018
Machine learning models are vulnerable to adversarial examples. An adversary modifies the input data such that humans still assign the same label, however, machine learning models misclassify it. Previous approaches in the literature demonstrated that adversarial examples can even be generated for the remotely hosted model.
Kulkarni, Mandar, Abubakar, Aria
openaire   +1 more source

Underutilization of syndrome‐specific ICD‐10 codes for genetic epilepsies: Implications for precision medicine

Epilepsia, EarlyView.
Abstract Syndrome‐specific International Classification of Diseases, 10th Revision (ICD‐10) codes have the potential to improve identification of patients for precision therapies, clinical trials, and research, yet their real‐world uptake is not well characterized.
Émile Moura Coelho da Silva, Tobias Brünger, Gary Taylor, Mousumi Sinha, Alison Merket, Anu Cherukara, Sunanjay Bajaj, Jessica Clark, Ludovica Montanucci, Emily A. Huth, Mariana Fauteux, Samden D. Lhatoo, Christian M. Boßelmann, Costin Leu, Rahil A. Tai, Dennis Lal   +15 more
wiley   +1 more source

Efficient multi-finger vein recognition using layer-wise progressive MobileNet fine-tuning and a Dense-Head Probabilistic Siamese Network. [PDF]

Sci Rep
Alaerjan AS, Mostafa AM, Mahmoud AA, Ezz M.   +3 more
europepmc   +1 more source