Results 61 to 70 of about 843 (158)

DoA Estimation for FMCW Radar by 3D-CNN

Sensors, 2021
A method of direction-of-arrival (DoA) estimation for FMCW (Frequency Modulated Continuous Wave) radar is presented. In addition to MUSIC, which is the popular high-resolution DoA estimation algorithm, deep learning has recently emerged as a very ...
Tzu-Hsien Sang, Feng-Tsun Chien, Chia-Chih Chang, Kuan-Yu Tseng, Bo-Sheng Wang, Jiun-In Guo   +5 more
doaj   +1 more source

Enhanced Lung Cancer Prediction via Integrated Multi‐Space Feature Adaptation, Collaborative Alignment and Disentanglement Learning

Engineering Reports, Volume 7, Issue 1, January 2025.
The research presents an enhanced lung cancer prediction model integrating AMSF‐L1ELM with Primitive Generation with Collaborative Relationship Alignment and Feature Disentanglement Learning. The model improves test accuracy, precision, recall, F1‐score, and ROC‐AUC across multiple domains in complex medical imaging data.
Abigail Kawama, Ronald Waweru Mwangi, Lawrence Nderu   +2 more
wiley   +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

HYPERSPECTRAL IMAGE CLASSIFICATION ON AMULTISCALE 3D CONVOLUTIONAL NEURAL NETWORK

Tạp chí Khoa học Đại học Đà Lạt
In the past decade, significant progress has been made in hyperspectral image (HSI) classification due to advances in deep learning techniques.
Duy Quy Thai, Thi Ngoc Thao Tran, Avirmed Enkhbat   +2 more
doaj   +1 more source

Strong Spatiotemporal Radar Echo Nowcasting Combining 3DCNN and Bi-Directional Convolutional LSTM

Atmosphere, 2020
In order to solve the existing problems of easy spatiotemporal information loss and low forecast accuracy in traditional radar echo nowcasting, this paper proposes an encoding-forecasting model (3DCNN-BCLSTM) combining 3DCNN and bi-directional ...
Suting Chen, Song Zhang, Huantong Geng, Yaodeng Chen, Chuang Zhang, Jinzhong Min   +5 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

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

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

Detecting anomalies in security cameras with 3DCNN and ConvLSTM

, 2023
Abstract This research introduces a novel deep learning-based approach for anomaly identification in surveillance films. The suggested approach is built on a deep network that has been taught to recognise objects and human activity in films. The technique was evaluated on five large-scale datasets from the real world, including UCF-Crime, XD ...
Esraa A. Mahareek, Eman K. El-Sayed, Nahed M. El-Desouky, Kamal A. El-Dahshan   +3 more
openaire   +1 more source