Results 161 to 170 of about 27,097 (268)

ECG‐TransCovNet: A hybrid transformer model for accurate arrhythmia detection using Electrocardiogram signals

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Abnormalities in the heart's rhythm, known as arrhythmias, pose a significant threat to global health, often leading to severe cardiac conditions and sudden cardiac deaths. Therefore, early and accurate detection of arrhythmias is crucial for timely intervention and potentially life‐saving treatment.
Hasnain Ali Shah, Faisal Saeed, Muhammad Diyan, Nouf Abdullah Almujally, Jae‐Mo Kang   +4 more
wiley   +1 more source

The Reward Positivity Tracks Positive Reward Prediction Errors From Feedback to Cues During Reinforcement Learning. [PDF]

Psychophysiology
Gao Y, Wilson R, Karpov G, Baker TE.
europepmc   +1 more source

Boosted unsupervised feature selection for tumor gene expression profiles

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract In an unsupervised scenario, it is challenging but essential to eliminate noise and redundant features for tumour gene expression profiles. However, the current unsupervised feature selection methods treat all samples equally, which tend to learn discriminative features from simple samples.
Yifan Shi, Kaixiang Yang, Mengzhi Wang, Zhiwen Yu, Huanqiang Zeng, Yang Hu   +5 more
wiley   +1 more source

Development and validation of a disease-syndrome integrated assessment model for AECOPD severity: protocol for a nationwide multicentre cross-sectional study. [PDF]

BMJ Open Respir Res
Zhang HL, Liu JM, Li Y, Wang LY, Jia PL, Yao ZX.   +5 more
europepmc   +1 more source

Short‐Term Multi‐Horizon Line Loss Rate Forecasting of a Distribution Network Using Attention‐GCN‐LSTM

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Accurately predicting line loss rates is crucial for effective management in distribution networks, particularly for short‐term multihorizon forecasts ranging from 1 hour to 1 week. In this study, we propose attention‐GCN–LSTM, a novel method that integrates graph convolutional networks (GCN), long short‐term memory (LSTM) and a three‐level ...
Jie Liu, Yijia Cao, Yong Li, Yixiu Guo, Wei Deng   +4 more
wiley   +1 more source

Cerebellum-inspired neural network of supervised learning with tensor-based sparse coding for multi-class classification. [PDF]

PLoS Comput Biol
Zhou R, Zhou D, Li S, Chen X.
europepmc   +1 more source

DrLS: Distortion‐Resistant Lossless Steganography via Colour Depth Interpolation

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT The lossless data steganography is to hide a certain amount of information into a container image. Previous lossless steganography methods fail to strike a balance between capacity, imperceptibility, accuracy, and robustness, commonly vulnerable to distortion on container images.
Youmin Xu, Xuanyu Zhang, Xiandong Meng, Jian Zhang   +3 more
wiley   +1 more source

Double‐Integration‐Enhanced Stochastic Gradient Descent Based on Neural Dynamics for Improving Generalisation

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Generalisation is a crucial aspect of deep learning, enabling models to perform well on unseen data. Currently, most optimisers that improve generalisation typically suffer from efficiency bottlenecks. This paper proposes a double‐integration‐enhanced stochastic gradient descent (DIESGD) optimiser, which treats the negative gradient as an ...
Ting Li, Longbang Wang, Jiexing Li, Jicheng Li   +3 more
wiley   +1 more source

Closed-form feedback-free learning with forward projection. [PDF]

Nat Commun
O'Shea R, Rajendran B.
europepmc   +1 more source

Robust Multi‐Source Batch Normalisation for Test‐Time Batch Adaptation

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Test‐Time Batch Adaptation (TTBA) aims to adapt a pre‐trained source model to small, unlabelled target batches at test time. The TTBA methods focus on adapting the pre‐trained model or the target data in a one‐to‐one alignment paradigm. However, these one‐to‐one alignment paradigms assume that the source domain may share the same knowledge ...
Xinlin Xiao, Xiangtao Zheng, Jianhua Tao, Xiaoqiang Lu   +3 more
wiley   +1 more source