{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T09:48:47Z","timestamp":1768816127293,"version":"3.49.0"},"reference-count":57,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2022,11,9]],"date-time":"2022-11-09T00:00:00Z","timestamp":1667952000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Joint Funds of the National Natural Science Foundation of China","award":["U20B2068"],"award-info":[{"award-number":["U20B2068"]}]},{"name":"Joint Funds of the National Natural Science Foundation of China","award":["No.GXXT-2020-015"],"award-info":[{"award-number":["No.GXXT-2020-015"]}]},{"name":"Joint Funds of the National Natural Science Foundation of China","award":["No.GXXT-2021-065"],"award-info":[{"award-number":["No.GXXT-2021-065"]}]},{"name":"Joint Funds of the National Natural Science Foundation of China","award":["KJ2020A0040"],"award-info":[{"award-number":["KJ2020A0040"]}]},{"name":"The University Synergy Innovation Program of Anhui Province","award":["U20B2068"],"award-info":[{"award-number":["U20B2068"]}]},{"name":"The University Synergy Innovation Program of Anhui Province","award":["No.GXXT-2020-015"],"award-info":[{"award-number":["No.GXXT-2020-015"]}]},{"name":"The University Synergy Innovation Program of Anhui Province","award":["No.GXXT-2021-065"],"award-info":[{"award-number":["No.GXXT-2021-065"]}]},{"name":"The University Synergy Innovation Program of Anhui Province","award":["KJ2020A0040"],"award-info":[{"award-number":["KJ2020A0040"]}]},{"name":"Natural Science Foundation of Anhui Higher Education Institution","award":["U20B2068"],"award-info":[{"award-number":["U20B2068"]}]},{"name":"Natural Science Foundation of Anhui Higher Education Institution","award":["No.GXXT-2020-015"],"award-info":[{"award-number":["No.GXXT-2020-015"]}]},{"name":"Natural Science Foundation of Anhui Higher Education Institution","award":["No.GXXT-2021-065"],"award-info":[{"award-number":["No.GXXT-2021-065"]}]},{"name":"Natural Science Foundation of Anhui Higher Education Institution","award":["KJ2020A0040"],"award-info":[{"award-number":["KJ2020A0040"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Factory extraction from satellite images is a key step in urban factory planning, and plays a crucial role in ecological protection and land-use optimization. However, factory extraction is greatly underexplored in the existing literature due to the lack of large-scale benchmarks. In this paper, we contribute a challenging benchmark dataset named SFE4395, which consists of 4395 satellite images acquired from Google Earth. The features of SFE4395 include rich multiscale factory instances and a wide variety of factory types, with diverse challenges. To provide a strong baseline for this task, we propose a novel bidirectional feature aggregation and compensation network called BACNet. In particular, we design a bidirectional feature aggregation module to sufficiently integrate multiscale features in a bidirectional manner, which can improve the extraction ability for targets of different sizes. To recover the detailed information lost due to multiple instances of downsampling, we design a feature compensation module. The module adds the detailed information of low-level features to high-level features in a guidance of attention manner. In additional, a point-rendering module is introduced in BACNet to refine results. Experiments using SFE4395 and public datasets demonstrate the effectiveness of the proposed BACNet against state-of-the-art methods.<\/jats:p>","DOI":"10.3390\/rs14225657","type":"journal-article","created":{"date-parts":[[2022,11,10]],"date-time":"2022-11-10T02:07:48Z","timestamp":1668046068000},"page":"5657","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Factory Extraction from Satellite Images: Benchmark and Baseline"],"prefix":"10.3390","volume":"14","author":[{"given":"Yifei","family":"Deng","sequence":"first","affiliation":[{"name":"Information Materials and Intelligent Sensing Laboratory of Anhui Province, School of Computer Science and Technology, Anhui University, Hefei 230039, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chenglong","family":"Li","sequence":"additional","affiliation":[{"name":"Information Materials and Intelligent Sensing Laboratory of Anhui Province, Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, School of Artificial Intelligence, Anhui University, Hefei 230601, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andong","family":"Lu","sequence":"additional","affiliation":[{"name":"Information Materials and Intelligent Sensing Laboratory of Anhui Province, School of Computer Science and Technology, Anhui University, Hefei 230039, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenjie","family":"Li","sequence":"additional","affiliation":[{"name":"Information Materials and Intelligent Sensing Laboratory of Anhui Province, School of Computer Science and Technology, Anhui University, Hefei 230039, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5948-5055","authenticated-orcid":false,"given":"Bin","family":"Luo","sequence":"additional","affiliation":[{"name":"Information Materials and Intelligent Sensing Laboratory of Anhui Province, School of Computer Science and Technology, Anhui University, Hefei 230039, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Yang, H., Wu, P., Yao, X., Wu, Y., Wang, B., and Xu, Y. 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