Results 51 to 60 of about 2,016 (190)

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

GS-BiFPN-YOLO: A Lightweight and Efficient Method for Segmenting Cotton Leaves in the Field

Agriculture
Instance segmentation of cotton leaves in complex field environments presents challenges including low accuracy, high computational complexity, and costly data annotation. This paper presents GS-BiFPN-YOLO, a lightweight instance segmentation method that
Weiqing Wu, Liping Chen
doaj   +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

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

FEA-Swin: Foreground Enhancement Attention Swin Transformer Network for Accurate UAV-Based Dense Object Detection

, 2022
UAV-based object detection has recently attracted a lot of attention due to its diverse applications. Most of the existing convolution neural network based object detection models can perform well in common object detection cases.
Zhang, Chaofan, Chaofan Zhang, Wang, Qi, Dai, Pangda, Qi Wang, Pangda Dai, Xu, Wenyu, Wenyu Xu   +7 more
core   +1 more source

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

Forest Fire Smoke Detection Based on Deep Learning Approaches and Unmanned Aerial Vehicle Images

, 2023
Wildfire poses a significant threat and is considered a severe natural disaster, which endangers forest resources, wildlife, and human livelihoods.
Azamjon Muminov, Soon-Young Kim
core   +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

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

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