{"title":"CFIPC-YOLO for Concealed Object Detection in Millimetre Wave Images","authors":"Huakun Zhang, Lin Guo, Deyue An, Odbal","doi":"10.1049/ell2.70367","DOIUrl":null,"url":null,"abstract":"<p>Human body security inspection is a critical task, and most existing methods rely on millimetre-wave images to detect concealed objects. However, detecting small and dim objects remains a significant challenge due to their subtle visual characteristics. To address this issue, this study proposes an efficient model, CFIPC-YOLO (contextual features integrated progressive convergence network based on the YOLOv8), which integrates local and contextual features into a progressively converging framework based on YOLO. Experimental results show that CFIPC-YOLO achieves a 5.3% improvement in AP50 compared to the YOLOv8 baseline, while simultaneously reducing the number of parameters by 17%, confirming the model's superior performance.</p>","PeriodicalId":11556,"journal":{"name":"Electronics Letters","volume":"61 1","pages":""},"PeriodicalIF":0.7000,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/ell2.70367","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Electronics Letters","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/ell2.70367","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Human body security inspection is a critical task, and most existing methods rely on millimetre-wave images to detect concealed objects. However, detecting small and dim objects remains a significant challenge due to their subtle visual characteristics. To address this issue, this study proposes an efficient model, CFIPC-YOLO (contextual features integrated progressive convergence network based on the YOLOv8), which integrates local and contextual features into a progressively converging framework based on YOLO. Experimental results show that CFIPC-YOLO achieves a 5.3% improvement in AP50 compared to the YOLOv8 baseline, while simultaneously reducing the number of parameters by 17%, confirming the model's superior performance.
期刊介绍:
Electronics Letters is an internationally renowned peer-reviewed rapid-communication journal that publishes short original research papers every two weeks. Its broad and interdisciplinary scope covers the latest developments in all electronic engineering related fields including communication, biomedical, optical and device technologies. Electronics Letters also provides further insight into some of the latest developments through special features and interviews.
Scope
As a journal at the forefront of its field, Electronics Letters publishes papers covering all themes of electronic and electrical engineering. The major themes of the journal are listed below.
Antennas and Propagation
Biomedical and Bioinspired Technologies, Signal Processing and Applications
Control Engineering
Electromagnetism: Theory, Materials and Devices
Electronic Circuits and Systems
Image, Video and Vision Processing and Applications
Information, Computing and Communications
Instrumentation and Measurement
Microwave Technology
Optical Communications
Photonics and Opto-Electronics
Power Electronics, Energy and Sustainability
Radar, Sonar and Navigation
Semiconductor Technology
Signal Processing
MIMO