{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T20:48:07Z","timestamp":1770756487429,"version":"3.50.0"},"reference-count":37,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T00:00:00Z","timestamp":1765497600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62276285"],"award-info":[{"award-number":["62276285"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"High tech Research and Development Center of the Ministry of Science and Technology\u2019s Science and Technology Innovation 2030-\u201cNew Generation Artificial Intelligence\u201d Major Project","award":["2021ZD0110600"],"award-info":[{"award-number":["2021ZD0110600"]}]},{"name":"Theme Case Library Project of the Degree and Graduate Education Development Center of the Ministry of Education"},{"name":"Postgraduate Research & Practice Innovation Program of Jiangsu Province","award":["SJCX25_2506"],"award-info":[{"award-number":["SJCX25_2506"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Imaging"],"abstract":"<jats:p>Object detection in complex environments, such as challenging lighting conditions, adverse weather, and target occlusions, poses significant difficulties for existing algorithms. To address these challenges, this study introduces a collaborative solution integrating improved CycleGAN-based data augmentation and an enhanced object detection framework, AS-YOLO. The improved CycleGAN incorporates a dual self-attention mechanism and spectral normalization to enhance feature capture and training stability. The AS-YOLO framework integrates a channel\u2013spatial parallel attention mechanism, an AFPN structure for improved feature fusion, and the Inner_IoU loss function for better generalization. The experimental results show that compared with YOLOv8n, mAP@0.5 and mAP@0.95 of the AS-YOLO algorithm have increased by 1.5% and 0.6%, respectively. After data augmentation and style transfer, mAP@0.5 and mAP@0.95 have increased by 14.6% and 17.8%, respectively, demonstrating the effectiveness of the proposed method in improving the performance of the model in complex scenarios.<\/jats:p>","DOI":"10.3390\/jimaging11120447","type":"journal-article","created":{"date-parts":[[2025,12,15]],"date-time":"2025-12-15T15:15:08Z","timestamp":1765811708000},"page":"447","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Enhanced Object Detection Algorithms in Complex Environments via Improved CycleGAN Data Augmentation and AS-YOLO Framework"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6743-4829","authenticated-orcid":false,"given":"Zhen","family":"Li","sequence":"first","affiliation":[{"name":"Ocean College, Jiangsu University of Science and Technology, Zhenjiang 212003, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuxuan","family":"Wang","sequence":"additional","affiliation":[{"name":"Ocean College, Jiangsu University of Science and Technology, Zhenjiang 212003, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4463-2192","authenticated-orcid":false,"given":"Lingzhong","family":"Meng","sequence":"additional","affiliation":[{"name":"Institute of Software Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenjuan","family":"Chu","sequence":"additional","affiliation":[{"name":"Ocean College, Jiangsu University of Science and Technology, Zhenjiang 212003, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-7797-151X","authenticated-orcid":false,"given":"Guang","family":"Yang","sequence":"additional","affiliation":[{"name":"Institute of Software Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,12,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Zhang, S., Wen, L., Bian, X., Lei, Z., and Li, S.Z. 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