Results 81 to 90 of about 1,313 (183)

Mouse Motion Behavior Recognition Based on DeepLabCut and Convolutional Long Short-Term Memory Network

, 2022
“MouseBehaviourDataset”  contains a 7 frame length and 1 frame interval mouse behaviour recognition dataset. "MouseKeypointDataset " contains the mouse keypoint detection dataset."BehaviourWeights" contain the weights of behavior recognition algorithms ...
Juncai Zhu (9651779)
core   +1 more source

Human activity recognition: A review of deep learning‐based methods

IET Computer Vision, Volume 19, Issue 1, January/December 2025.
Human Activity Recognition (HAR) covers methods for automatically identifying human activities from a stream of data. End‐users of HAR methods cover a range of sectors, including health, self‐care, amusement, safety and monitoring. In this survey, the authors provide a thorough overview of deep learning based and detailed analysis of work that was ...
Sanjay Jyoti Dutta, Tossapon Boongoen, Reyer Zwiggelaar   +2 more
wiley   +1 more source

Computer-aided diagnosis based on 3D deep convolutional neural network system using novel 3D magnetic resonance imaging sequences for high-grade prostate cancer

Current Urology
. Background. With the rising incidence of prostate cancer (PCa), there is a global demand for assistive tools that aid in the diagnosis of high-grade PCa.
Ryo Oka, Bochong Li, Seiji Kato, Takanobu Utsumi, Takumi Endo, Naoto Kamiya, Toshiya Nakaguchi, Hiroyoshi Suzuki   +7 more
doaj   +1 more source

A Lightweight Dual‐Branch Meta‐Learner for Few‐Shot HSI Classification With Cross‐Domain Adaptation

IET Computer Vision, Volume 19, Issue 1, January/December 2025.
We refine the 3D attention network TGAN into TGAN2 (3D ghost attention network v2) by replacing the original ghost blocks with ghost‐V2 modules and enlarging the receptive field to capture global context. We propose a dual‐adjustment mode (comprising intracorrection (IC) and interalignment (IA)) to generate robust class prototypes and mitigate domain ...
Junqi Yao, Yonghui Yang, Ou Yang, Qingtian Wu   +3 more
wiley   +1 more source

Few‐shot real scenes convolutional anchor clustering twin network for hyperspectral image classification

IET Image Processing, Volume 19, Issue 1, January/December 2025.
The authors propose a new supervised contrastive learning framework (FSSCL‐OSC) that can achieve open‐set classification of hyperspectral images in scenarios with very few sample sizes. Experimental results on three classical HSI datasets show that FSSCL‐OSC provides a significant improvement over existing methods, under a sample size of only 10%, the ...
Xiangshan Zhou, Xiaoyi Tong, Xuchuan Zhou, Lin Wang, Lei Zhang, Jie Zhou, Su Qin   +6 more
wiley   +1 more source

Data_Sheet_1_Resting state network mapping in individuals using deep learning.DOCX

, 2023
IntroductionResting state functional MRI (RS-fMRI) is currently used in numerous clinical and research settings. The localization of resting state networks (RSNs) has been utilized in applications ranging from group analysis of neurodegenerative diseases
Evan M. Gordon (14394084), Ryan V. Raut (14394078), Karin L. Meeker (14394081), Ki Yun Park (9193166), Eric C. Leuthardt (7348868), Abraham Z. Snyder (8027606), John J. Lee (7972976), Beau M. Ances (8294550), Joshua S. Shimony (8027603), Patrick H. Luckett (14394075)   +9 more
core   +1 more source

3DC-BiL: a temporal enhanced model combining three-dimensional convolutional neural network and bidirectional long short-term memory networks for electroencephalography emotion recognition [PDF]

PeerJ Computer Science
Electroencephalography (EEG) signals are physiological signals that directly reflect the brain’s electrical activity, holding significant research value in the field of emotion recognition.
Junshuai Zhang, Zhengping Li, Weizhi Ma, Lijun Wang, Yuwen Hao, Xiaoxue Li   +5 more
doaj   +2 more sources

A Comprehensive Survey of Advancement in Lip Reading Models: Techniques and Future Directions

IET Image Processing, Volume 19, Issue 1, January/December 2025.
Efficient and accurate lip reading models increase information processing and decision‐making by understanding massive quantities of text. Lip reading can make communication more inclusive, especially for hearing‐impaired people, according to this study. From 2020 to 2024, researchers track lip‐reading algorithm progress.
Sampada Deshpande, Kalyani Shirsath, Amey Pashte, Pratham Loya, Sandip Shingade, Vijay Sambhe   +5 more
wiley   +1 more source

SAT-3DCNN: Unifying Spectral Attention and Transformer-Based Modeling for Hyperspectral Remote Sensing

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Hyperspectral imaging (HSI) has emerged as a transformative technology across diverse fields, including mineral exploration, precision agriculture, environmental surveillance, and medical diagnostics.
Ahmad Almadhor, Abdullah Al Hejaili, Nejib Ghazouani, Natalia Kryvinska   +3 more
doaj   +1 more source

FENet: A Physics‐Informed Dynamics Prediction Model of Pantograph‐Catenary Systems in Electric Railway

IET Intelligent Transport Systems, Volume 19, Issue 1, January/December 2025.
In this manuscript, we proposed physics‐informed surrogate model, called FENet, for the first time to solve the interaction of pantograph‐catenary system. In recent years, much progress has been achieved in PCS modelling solutions. Existing solutions, however, suffer from two significant limitations: 1) An urgent concern arises regarding the ...
Wenping Chu, Hui Wang, Yang Song, Zhigang Liu   +3 more
wiley   +1 more source