{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T00:41:45Z","timestamp":1760488905099,"version":"build-2065373602"},"reference-count":32,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2019,9,8]],"date-time":"2019-09-08T00:00:00Z","timestamp":1567900800000},"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":["61725105;41801349"],"award-info":[{"award-number":["61725105;41801349"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Gusu Innovation Talent Foundation of Suzhou","award":["ZXT2017002"],"award-info":[{"award-number":["ZXT2017002"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In recent years, deep learning has led to a remarkable breakthrough in object detection in remote sensing images. In practice, two-stage detectors perform well regarding detection accuracy but are slow. On the other hand, one-stage detectors integrate the detection pipeline of two-stage detectors to simplify the detection process, and are faster, but with lower detection accuracy. Enhancing the capability of feature representation may be a way to improve the detection accuracy of one-stage detectors. For this goal, this paper proposes a novel one-stage detector with enhanced capability of feature representation. The enhanced capability benefits from two proposed structures: dual top-down module and dense-connected inception module. The former efficiently utilizes multi-scale features from multiple layers of the backbone network. The latter both widens and deepens the network to enhance the ability of feature representation with limited extra computational cost. To evaluate the effectiveness of proposed structures, we conducted experiments on horizontal bounding box detection tasks on the challenging DOTA dataset and gained 73.49% mean Average Precision (mAP), achieving state-of-the-art performance. Furthermore, our method ran significantly faster than the best public two-stage detector on the DOTA dataset.<\/jats:p>","DOI":"10.3390\/rs11182095","type":"journal-article","created":{"date-parts":[[2019,9,9]],"date-time":"2019-09-09T04:12:40Z","timestamp":1568002360000},"page":"2095","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":31,"title":["Enhanced Feature Representation in Detection for Optical Remote Sensing Images"],"prefix":"10.3390","volume":"11","author":[{"given":"Kun","family":"Fu","sequence":"first","affiliation":[{"name":"School of Microelectronics, University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Key Laboratory of Network Information System Technology, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"Institute of Electronics, Chinese Academy of Sciences, Suzhou 215000, China"}]},{"given":"Zhuo","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Microelectronics, University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Key Laboratory of Network Information System Technology, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China"}]},{"given":"Yue","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"Key Laboratory of Network Information System Technology, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China"}]},{"given":"Xian","family":"Sun","sequence":"additional","affiliation":[{"name":"Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Key Laboratory of Network Information System Technology, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China"}]}],"member":"1968","published-online":{"date-parts":[[2019,9,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.isprsjprs.2016.03.014","article-title":"A survey on object detection in optical remote sensing images","volume":"117","author":"Cheng","year":"2016","journal-title":"ISPRS J. 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