{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T09:42:19Z","timestamp":1769593339706,"version":"3.49.0"},"reference-count":9,"publisher":"SAGE Publications","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IFS"],"published-print":{"date-parts":[[2024,4,18]]},"abstract":"<jats:p>Military object military object detection technology serves as the foundation and critical component for reconnaissance and command decision-making, playing a significant role in information-based and intelligent warfare. However, many existing military object detection models focus on exploring deeper and more complex architectures, which results in models with a large number of parameters. This makes them unsuitable for inference on mobile or resource-constrained combat equipment, such as combat helmets and reconnaissance Unmanned Aerial Vehicles (UAVs). To tackle this problem, this paper proposes a lightweight detection framework. A CSP-GhostnetV2 module is proposed in our method to make the feature extraction network more lightweight while extracting more effective information. Furthermore, to fuse multiscale information in low-computational scenarios, GSConv and the proposed CSP-RepGhost are used to form a lightweight feature aggregation network. The experimental results demonstrate that our proposed lightweight model has significant advantages in detection accuracy and efficiency compared to other detection algorithms.<\/jats:p>","DOI":"10.3233\/jifs-234127","type":"journal-article","created":{"date-parts":[[2024,3,5]],"date-time":"2024-03-05T11:30:27Z","timestamp":1709638227000},"page":"10329-10343","source":"Crossref","is-referenced-by-count":1,"title":["Towards lightweight military object detection"],"prefix":"10.1177","volume":"46","author":[{"given":"Zhigang","family":"Li","sequence":"first","affiliation":[{"name":"College of Artificial Intelligence, North China University of Science and Technology, Tangshan, Hebei, P.R. China"},{"name":"Key Laboratory of Industrial Intelligent Perception, Tangshan, Hebei, P.R. China"}]},{"given":"Wenhao","family":"Nian","sequence":"additional","affiliation":[{"name":"College of Artificial Intelligence, North China University of Science and Technology, Tangshan, Hebei, P.R. China"},{"name":"Key Laboratory of Industrial Intelligent Perception, Tangshan, Hebei, P.R. China"}]},{"given":"Xiaochuan","family":"Sun","sequence":"additional","affiliation":[{"name":"College of Artificial Intelligence, North China University of Science and Technology, Tangshan, Hebei, P.R. China"},{"name":"Key Laboratory of Industrial Intelligent Perception, Tangshan, Hebei, P.R. China"}]},{"given":"Shujie","family":"Li","sequence":"additional","affiliation":[{"name":"College of Artificial Intelligence, North China University of Science and Technology, Tangshan, Hebei, P.R. China"}]}],"member":"179","reference":[{"issue":"2","key":"10.3233\/JIFS-234127_ref1","doi-asserted-by":"crossref","first-page":"1045","DOI":"10.1007\/s00500-021-05912-0","article-title":"Military object detection in defense using multi-level capsule networks","volume":"27","author":"Janakiramaiah","year":"2023","journal-title":"Soft Computing"},{"key":"10.3233\/JIFS-234127_ref2","doi-asserted-by":"crossref","first-page":"99897","DOI":"10.1109\/ACCESS.2022.3207153","article-title":"Military vehicle object detection based on hierarchical feature representation and refined localization","volume":"10","author":"Ouyang","year":"2022","journal-title":"IEEE Access"},{"key":"10.3233\/JIFS-234127_ref3","doi-asserted-by":"crossref","unstructured":"Zhang Y. , Ye L. , Fang L. , Zhong W. , Hu F. and Zhang Q. , Benchmarking the robustness of object detection based on near-real military scenes, Wireless Communications and Mobile Computing 2022 (2022).","DOI":"10.1155\/2022\/5884625"},{"issue":"23","key":"10.3233\/JIFS-234127_ref5","doi-asserted-by":"crossref","first-page":"12236","DOI":"10.3390\/app122312236","article-title":"A military object detection model of uav reconnaissance image and feature visualization","volume":"12","author":"Liu","year":"2022","journal-title":"Applied Sciences"},{"issue":"20","key":"10.3233\/JIFS-234127_ref7","doi-asserted-by":"crossref","first-page":"3263","DOI":"10.3390\/electronics11203263","article-title":"A lightweight military target detection algorithm based on improved yolov5","volume":"11","author":"Du","year":"2022","journal-title":"Electronics"},{"issue":"2","key":"10.3233\/JIFS-234127_ref15","doi-asserted-by":"crossref","first-page":"955","DOI":"10.1609\/aaai.v35i2.16179","article-title":"Yolobile: Real-time object detection on mobile devices via compression-compilation co-design, in","volume":"35","author":"Cai","year":"2021","journal-title":"Proceedings of the AAAI Conference on Artificial Intelligence"},{"key":"10.3233\/JIFS-234127_ref24","unstructured":"Wang R.J. , Li X. and Ling C.X. , Pelee: A real-time object detection system on mobile devices, Advances in Neural Information Processing Systems 31 (2018)."},{"issue":"1","key":"10.3233\/JIFS-234127_ref27","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1109\/LSP.2018.2825959","article-title":"Detection of people with camouflage pattern via dense deconvolution network","volume":"26","author":"Zheng","year":"2018","journal-title":"IEEE Signal Processing Letters"},{"key":"10.3233\/JIFS-234127_ref29","unstructured":"Ren S. , He K. , Girshick R. and Sun J. , Faster r-cnn: Towards real-time object detection with region proposal networks, Advances in Neural Information Processing Systems 28 (2015)."}],"container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/JIFS-234127","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,27]],"date-time":"2026-01-27T18:50:04Z","timestamp":1769539804000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/JIFS-234127"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,4,18]]},"references-count":9,"journal-issue":{"issue":"4"},"URL":"https:\/\/doi.org\/10.3233\/jifs-234127","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"value":"1064-1246","type":"print"},{"value":"1875-8967","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,4,18]]}}}