Results 41 to 50 of about 843 (158)

Unsupervised 3D Reconstruction with Multi-Measure and High-Resolution Loss

Sensors, 2022
Multi-view 3D reconstruction technology based on deep learning is developing rapidly. Unsupervised learning has become a research hotspot because it does not need ground truth labels.
Yijie Zheng, Jianxin Luo, Weiwei Chen, Yanyan Zhang, Haixun Sun, Zhisong Pan   +5 more
doaj   +1 more source

Rethinking 3D-CNN in Hyperspectral Image Super-Resolution

Remote Sensing, 2023
Recently, CNN-based methods for hyperspectral image super-resolution (HSISR) have achieved outstanding performance. Due to the multi-band property of hyperspectral images, 3D convolutions are natural candidates for extracting spatial–spectral ...
Ziqian Liu, Wenbing Wang, Qing Ma, Xianming Liu, Junjun Jiang   +4 more
doaj   +1 more source

Clean fishing: Construction of prediction model for high-catch Antarctic krill (Euphausia superba) fishing grounds based on deep learning and dynamic sliding window methods

Ecological Informatics
Achieving energy-efficient, precise, and overall efficient production of Antarctic krill (Euphausia superba) is critical for realizing sustainable and ecological fisheries in the context of ongoing natural and anthropogenic climate change. In this study,
Haibin Han, Bohui Jiang, Hongliang Huang, Yang Li, Jianghua Sui, Guoqing Zhao, Yuhan Wang, Heng Zhang, Shenglong Yang, Yongchuang Shi   +9 more
doaj   +1 more source

Deep Learning for Brain MRI Confirms Patterned Pathological Progression in Alzheimer's Disease

Advanced Science, 2023
Deep learning (DL) on brain magnetic resonance imaging (MRI) data has shown excellent performance in differentiating individuals with Alzheimer's disease (AD).
Dan Pan, An Zeng, Baoyao Yang, Gangyong Lai, Bing Hu, Xiaowei Song, Tianzi Jiang, Alzheimer's Disease Neuroimaging Initiative (ADNI)   +7 more
doaj   +1 more source

Automatic Assessment of ASPECTS Using Diffusion-Weighted Imaging in Acute Ischemic Stroke Using Recurrent Residual Convolutional Neural Network

Diagnostics, 2020
The early detection and rapid quantification of acute ischemic lesions play pivotal roles in stroke management. We developed a deep learning algorithm for the automatic binary classification of the Alberta Stroke Program Early Computed Tomographic Score (
Luu-Ngoc Do, Byung Hyun Baek, Seul Kee Kim, Hyung-Jeong Yang, Ilwoo Park, Woong Yoon   +5 more
doaj   +1 more source

Enhancing Rail Transit Safety: Edge Computing‐Based Driver State Monitoring System

IET Intelligent Transport Systems, Volume 20, Issue 1, January/December 2026.
This article presents an edge computing‐based driver state monitoring system designed to enhance rail transit safety by analyzing real‐time data on driver identity, posture, and behavior. Leveraging facial recognition and AI‐driven detection methods, the system integrates edge and cloud computing to promptly identify unsafe conditions, enabling ...
Yiqing Liu, Gaoyun Cheng, Binbin Yuan, Hongyu Sun, Edward Stewart, Zhe Fu, Zongru Ma, Ning Zhao   +7 more
wiley   +1 more source

GSDF‐Gait: A GCN and Self‐Attention Dynamic Fusion Network for Gait‐Based Person Recognition

Applied Computational Intelligence and Soft Computing, Volume 2026, Issue 1, 2026.
Graph convolutional networks (GCNs) are extensively used for skeleton‐based gait recognition. Nevertheless, despite significant improvements, a substantial challenge lies in the restricted receptive field of GCNs. However, separate structural joints could also reveal a notably important correlation.
Md. Khaliluzzaman, Kaushik Deb, Nasimul Noman   +2 more
wiley   +1 more source

Human Action Representation Learning Using an Attention-Driven Residual 3DCNN Network

Algorithms, 2023
The recognition of human activities using vision-based techniques has become a crucial research field in video analytics. Over the last decade, there have been numerous advancements in deep learning algorithms aimed at accurately detecting complex human actions in video streams.
Hayat Ullah, Arslan Munir
openaire   +2 more sources

Decrypting cancer's spatial code: from single cells to tissue niches

Molecular Oncology, Volume 19, Issue 12, Page 3465-3485, December 2025.
Spatial transcriptomics maps gene activity across tissues, offering powerful insights into how cancer cells are organised, switch states and interact with their surroundings. This review outlines emerging computational, artificial intelligence (AI) and geospatial approaches to define cell states, uncover tumour niches and integrate spatial data with ...
Cenk Celik, Shi Pan, Eloise Withnell, Hou Wang Lam, Maria Secrier   +4 more
wiley   +1 more source

Hyperspectral Imaging: The Intelligent Eye to Uncover the Password of Plant Science

Modern Agriculture, Volume 3, Issue 2, December 2025.
Hyperspectral imaging (HSI) has emerged as a powerful non‐destructive technique for characterisation of the plant phenotype and physiological traits. The ongoing development of cost‐effective hardware, coupled with standardised acquisition protocols and open‐access spectral libraries, is accelerating its integration with multi‐omics approaches to ...
Jingyan Song, Haifeng Liang, Bingjie Lu, Jing Guo, Yuan Gao, Xiao Hu, Manlin Yang, Xiaofan Li, Zhenyu Wang, Yongqi Chen, Yinyin Zhang, Shen Su, Zhangyun Gao, Shijie Li, Ping Chen, Jing Wang, Wanneng Yang, Hui Feng   +17 more
wiley   +1 more source