{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T21:14:17Z","timestamp":1784236457170,"version":"3.55.0"},"reference-count":47,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2021,1,28]],"date-time":"2021-01-28T00:00:00Z","timestamp":1611792000000},"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":["61673017"],"award-info":[{"award-number":["61673017"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61403398"],"award-info":[{"award-number":["61403398"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007128","name":"Natural Science Foundation of Shaanxi Province","doi-asserted-by":"publisher","award":["2018ZDXM-GY-039"],"award-info":[{"award-number":["2018ZDXM-GY-039"]}],"id":[{"id":"10.13039\/501100007128","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Road extraction from remote sensing images is of great significance to urban planning, navigation, disaster assessment, and other applications. Although deep neural networks have shown a strong ability in road extraction, it remains a challenging task due to complex circumstances and factors such as occlusion. To improve the accuracy and connectivity of road extraction, we propose an inner convolution integrated encoder-decoder network with the post-processing of directional conditional random fields. Firstly, we design an inner convolutional network which can propagate information slice-by-slice within feature maps, thus enhancing the learning of road topology and linear features. Additionally, we present the directional conditional random fields to improve the quality of the extracted road by adding the direction of roads to the energy function of the conditional random fields. The experimental results on the Massachusetts road dataset show that the proposed approach achieves high-quality segmentation results, with the F1-score of 84.6%, which outperforms other comparable \u201cstate-of-the-art\u201d approaches. The visualization results prove that the proposed approach is able to effectively extract roads from remote sensing images and can solve the road connectivity problem produced by occlusions to some extent.<\/jats:p>","DOI":"10.3390\/rs13030465","type":"journal-article","created":{"date-parts":[[2021,1,28]],"date-time":"2021-01-28T11:54:53Z","timestamp":1611834893000},"page":"465","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":47,"title":["Road Extraction from Remote Sensing Images Using the Inner Convolution Integrated Encoder-Decoder Network and Directional Conditional Random Fields"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3788-9494","authenticated-orcid":false,"given":"Shuyang","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Information Engineering, Xi\u2019an Hi-Tech Research Institute, Xi\u2019an 710025, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaodong","family":"Mu","sequence":"additional","affiliation":[{"name":"Department of Information Engineering, Xi\u2019an Hi-Tech Research Institute, Xi\u2019an 710025, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dongfang","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Control Engineering, Xi\u2019an Hi-Tech Research Institute, Xi\u2019an 710025, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hao","family":"He","sequence":"additional","affiliation":[{"name":"Department of Measurement and Control, Qingzhou Hi-Tech Research Institute, Qingzhou 262500, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peng","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Information Engineering, Xi\u2019an Hi-Tech Research Institute, Xi\u2019an 710025, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,1,28]]},"reference":[{"key":"ref_1","first-page":"271","article-title":"A review of road extraction from remote sensing images","volume":"3","author":"Wang","year":"2016","journal-title":"J. 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