Results 51 to 60 of about 2,335 (188)

Multi‐Head Bias Fusion and Adaptive Aligned Gradient of Multi‐Task Learning for Joint Human Detection, Segmentation and Pose Estimation

IET Image Processing, Volume 20, Issue 1, January/December 2026.
YOLODSP incorporates multi‐task heads and introduces a BiasFusion module to predict the offsets of pose estimation and segmentation. With an overall average precision difference of no more than 1% relative to the combination of multiple single‐task methods, YOLODSP reduces the computational load by 35.2%, 38.8% and 40.5% on the YOLOv8‐nano, YOLOv8 ...
Feng Lu, Peng Ye, Yaowen Zhang, Ning Lu, Jinsheng Chen, Youchun Xu   +5 more
wiley   +1 more source

AHD‐YOLO: An Adaptive Hybrid Dynamic Network for Building Damage Detection

IET Image Processing, Volume 20, Issue 1, January/December 2026.
To address the issues of limited detection accuracy and high computational resource consumption in current deep learning‐based building damage detection, we propose a novel framework, AHD YOLO, built upon YOLOv11. AHD YOLO achieves an optimal balance between detection performance and computational resource efficiency, demonstrating strong potential for
Min Li, Tao Xu, Yinping Jiang, Peiyong Ji, Jingqi Hu, Wenlong Lui, Xuejian Ji, Ruiqiang Guo   +7 more
wiley   +1 more source

Vehicle Paint Defect Detection Based on Improved YOLOv8 [PDF]

Jisuanji gongcheng
To address the issues of low accuracy in vehicle paint defect detection, excessive parameters in detection algorithms, and the uneven distribution of easy and hard samples, a vehicle paint detection method based on an improved YOLOv8 is proposed.
HAO Yousheng, WEN Zhenhui, FENG Xiaoxi, DENG Zehua, HUANG Qingbao
doaj   +1 more source

SSGA‐YOLO: A Lightweight Sonar Image Object Detection Network With Efficient Convolution and Acoustic‐Aware Attention for Embedded Systems

IET Image Processing, Volume 20, Issue 1, January/December 2026.
We propose SSGA‐YOLO, an efficient underwater sonar image detector designed for deployment on embedded AI platforms. By introducing a lightweight S‐Net backbone, Efficient Group Shuffle Convolution (EGSConv) and Lightweight Shuffle‐Aware Group Attention (LSGA), our model achieves a strong balance between accuracy and efficiency, reducing parameters and
Yan Liu, Gan Yan, Tong Chen, Guanying Huo   +3 more
wiley   +1 more source

Application of Feature Re‐Calibration Network Combined With Transformer in MRI Brain Tumour Diagnosis

IET Image Processing, Volume 20, Issue 1, January/December 2026.
In the context of Smart Healthcare, to assist doctors in diagnosing brain tumours and reduce the medical burden, this paper proposes a lightweight feature re‐calibration network (FRCNet). Aiming at the problem of similar and difficult classification of multi‐class brain tumours, partially transformer block (PTB), a CNN‐Transformer parallel dual‐branch ...
Jiyuan Yan, Moji Pan, Guoxiang Hua, Weiwei Li, Xing Huang, Yehcheng Chen, Zhaorui Zheng   +6 more
wiley   +1 more source

BiFPN-CBAM structure framework.

The automatic detection of the degree of surface corrosion on metal structures is of significant importance for assessing structural damage and safety.
Zhitong Jia (17709113), Lingzhi Wu (133076), Zhendong Cui (18340284), Mingjiao Fu (18340281)   +3 more
core   +1 more source

DenseDuckMOT: A Real-Time Detection-Tracking Coupled Counting Framework for Complex Avicultural Environments. [PDF]

Animals (Basel)
The Liancheng White Duck is a nationally protected breed in China, but its high-density farming environment poses significant challenges for target detection and behavior recognition, particularly due to occlusion, motion blur, and flock aggregation ...
Xie J, Wu J, Chen L, Cao Y, Chen Z, Lu M, Lin Y, Tu C, Wang W, Lin J.   +9 more
europepmc   +2 more sources

USIF‐Net: U‐Shaped Symmetrical Interactive Fusion Network for Industrial Surface Defect Detection

IET Image Processing, Volume 20, Issue 1, January/December 2026.
This paper proposes USIF‐Net to address challenges in industrial defect detection such as inter‐defect similarity, weak small‐target semantics, and multi‐scale variations. The model incorporates LGFE‐Net for local‐global feature extraction, a U‐shaped PIC‐Net for cross‐level interactive fusion, and AFFM for adaptive feature integration to mitigate ...
Laomo Zhang, Zeyu Yang, Ying Ma, Guowei Li   +3 more
wiley   +1 more source

Enhanced YOLOv9s‐Based Surface Defect Detection in Filter Images via Generative Data Augmentation and Model Optimisation

IET Image Processing, Volume 20, Issue 1, January/December 2026.
This study proposes a dataset generation method based on StyleGAN3 and a filter surface defect detection algorithm, SCP‐YOLO, based on an improved YOLOv9s. By generating filter defect images using StyleGAN3 and combining them with filter images, we create a large‐scale dataset. Based on YOLOv9, a new network was proposed.
Yinxiao Liu, Xiaojuan Wei, Mengxu Chen, Guojun Liu, Chunxia Zhao, Maoyuan Zhang, Yunfeng Guo, Pengcheng Zhao, Run An   +8 more
wiley   +1 more source

A Multi‐Scale Detection Network With Uncertainty Modelling for Infrared Small Target Detection

IET Image Processing, Volume 20, Issue 1, January/December 2026.
We propose MMSNet to tackle the feature degradation and optimisation instability inherent in infrared small target detection. By synergising a lightweight multi‐scale depthwise fusion module with a novel quality‐aware MS‐NWD loss function, our method effectively captures weak targets under complex backgrounds.
Shan Jiang, Haohan Yang, Hongwei Yang, Cheng Han, Xu Zheng   +4 more
wiley   +1 more source