Reset
Showing 20 of 210 academic articles

Segmentation of muscle tissue in computed tomography images at the level of the L3 vertebra

A. R. Teplyakova, R. V. Shershnev, S. O. Starkov, V. A. Kukarskaya • Научно-технический вестник информационных технологий, механики и оптики (2024)

With the increasing routine workload on radiologists associated with the need to analyze large numbers of images, there is a need to automate part of the analysis process. Sarcopenia is a condition in which there is a loss of muscle mass. T...

DOAJ Open Access (DOAJ) DOI: 10.17586/2226-1494-2024-24-1-124-132

Improved U-Net Model for Road Crack Detection Based on Residual and Attention Mechanism

YU Haiyang, JING Peng, ZHANG Wentao, XIE Saifei, HUA Zhihua, SONG Caoyuan • Jisuanji gongcheng (2023)

Road cracks are an important part of road safety detection,and with the development of deep learning and computer vision,methods for extracting crack information in road images using deep learning methods are maturing.Existing deep learning...

DOAJ Open Access (DOAJ) DOI: 10.19678/j.issn.1000-3428.0064952

Effectual pre-processing with quantization error elimination in pose detector with the aid of image-guided progressive graph convolution network (IGP-GCN) for multi-person pose estimation

Jhansi Rani Challapalli, Nagaraju Devarakonda • Machine Learning: Science and Technology (2023)

Multi-person pose estimation (MPE) remains a significant and intricate issue in computer vision. This is considered the human skeleton joint identification issue and resolved by the joint heat map regression network lately. Learning robust ...

DOAJ Open Access (DOAJ) DOI: 10.1088/2632-2153/acc9fc

A lightweight fully convolutional neural network for efficient and accurate tunnel crack detection

Hao Huang, G.T.S. Ho, V. Tang, E.W.H. Chow et al. • Journal of Advanced Research (2026)

Introduction: Crack damage is a significant issue in tunnel environments, requiring efficient and reliable detection to ensure structural integrity. Many existing solutions are computationally expensive, making them unsuitable for the tight...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jare.2025.11.052

Multimodal Phase-Space Dynamics Fusion for Robust Ischemia Screening: An Edge-AI Paradigm with SERF Magnetocardiography

Keyi Li, Xiangyang Zhou, Yifan Jia, Ruizhe Wang et al. • Biosensors (2026)

Background: Myocardial ischemia (MI) is a major cause of morbidity and mortality worldwide and requires timely and reliable detection. Although Spin-Exchange Relaxation-Free (SERF) magnetocardiography (MCG) provides femtotesla-level sensiti...

DOAJ Open Access (DOAJ) DOI: 10.3390/bios16040228

Resting Posture Recognition Method for Suckling Piglets Based on Piglet Posture Recognition (PPR)–You Only Look Once

Jinxin Chen, Luo Liu, Peng Li, Wen Yao et al. • Agriculture (2025)

The resting postures of piglets are crucial indicators for assessing their health status and environmental comfort. This study proposes a resting posture recognition method for piglets during lactation based on the PPR-YOLO model, aiming to...

DOAJ Open Access (DOAJ) DOI: 10.3390/agriculture15030230

Aphid-ResNetSwin: An Image Recognition Method with Improved Attention Mechanism for Graded Identification of <i>Myzus persicae</i>

Jinzhou Luo, Jiazhao Sun, Xiaoli Hao, Heng Liu et al. • Insects (2026)

Myzus persicae is the most devastating piercing-sucking pest threatening tobacco production. Precise quantification of infestation severity is a prerequisite for precision pest management, making the integration of visual image analysis hig...

DOAJ Open Access (DOAJ) DOI: 10.3390/insects17030305

Attention mechanisms in computer vision: A survey

Meng-Hao Guo, Tian-Xing Xu, Jiangjiang Liu, Zheng-Ning Liu et al. • Computational Visual Media (2022)

Humans can naturally and effectively find salient regions in complex scenes. Motivated by this observation, attention mechanisms were introduced into computer vision with the aim of imitating this aspect of the human visual system. Such an ...

OPENALEX cc-by DOI: https://doi.org/10.1007/s41095-022-0271-y

Multi-scale attention and collaborative fusion for enhanced RGB-D salient object detection in weld quality inspection

Zhiwen Xiong, Yuanchun Li • Scientific Reports (2026)

Abstract Salient object detection (SOD) plays a crucial role in computer vision by mimicking human visual attention to identify and segment the most prominent objects in a scene. The advent of depth sensing technologies has propelled RGB-D ...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-026-56237-7

Low illumination image enhancement algorithm of CycleGAN coal mine based on attention mechanism and Dilated convolution

Yuanbin WANG, Yaru GUO, Jia LIU, Xu WANG et al. • Meitan kexue jishu (2024)

The complex underground environment, filled with a large amount of dust and water vapor, and uneven illumination of artificial light source, leads to problems such as low illumination and loss of detail features in images collected by under...

DOAJ Open Access (DOAJ) DOI: 10.12438/cst.2023-1597

Retrieval of carbon dioxide vertical concentration profiles from satellite data using artificial neural networks

A. Roberto Carvalho, F. Manoel Ramos, J. Carlos Carvalho • Trends in Computational and Applied Mathematics (2010)

Abstract. In this paper, we derive vertical distributions of carbon dioxide atmospheric concentration from satellite data using a retrieval algorithm based on an artificial neural network (ANN) technique. Sensitivity studies were made to se...

DOAJ Open Access (DOAJ) DOI: 10.5540/tema.2010.011.03.0205

Logical Reasoning Based on Residual Attention Multi-scale Relation Network

XIONG Zhongmin, ZENG Qi, LU Peng, WANG Zhenhua, ZHENG Zongsheng • Jisuanji gongcheng (2023)

Logical reasoning is the ability to perceive patterns and connections between visual elements. Endowing computers with human-like reasoning ability is a critical area of research;state-of-the-art deep neural networks have achieved superhuma...

DOAJ Open Access (DOAJ) DOI: 10.19678/j.issn.1000-3428.0064591

3D Octave and 2D Vanilla Mixed Convolutional Neural Network for Hyperspectral Image Classification with Limited Samples

Yuchao Feng, Jianwei Zheng, Mengjie Qin, Cong Bai et al. • Remote Sensing (2021)

Owing to the outstanding feature extraction capability, convolutional neural networks (CNNs) have been widely applied in hyperspectral image (HSI) classification problems and have achieved an impressive performance. However, it is well know...

DOAJ Open Access (DOAJ) DOI: 10.3390/rs13214407

Detection of short-term peaks in VLF/LF signals around the time of gamma-ray burst detections using deep learning

Sarnovský M., Nina A., Popović L.Č., Srećković V. et al. • Serbian Astronomical Journal (2026)

Gamma-ray bursts (GRBs) are recognized as the most energetic and luminous astrophysical phenomena whose high-energy photons can ionize atmospheric particles and thus affect electrical conductivity. Consequently, electromagnetic waves ...

DOAJ Open Access (DOAJ) DOI: 10.2298/SAJ2612107S