{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T15:44:16Z","timestamp":1776181456641,"version":"3.50.1"},"reference-count":54,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2021,7,9]],"date-time":"2021-07-09T00:00:00Z","timestamp":1625788800000},"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":["51979233"],"award-info":[{"award-number":["51979233"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Technology of the People\u2019s Republic of China","award":["2017YFC0403203"],"award-info":[{"award-number":["2017YFC0403203"]}]},{"DOI":"10.13039\/501100013314","name":"111 Project","doi-asserted-by":"publisher","award":["No. B12007"],"award-info":[{"award-number":["No. B12007"]}],"id":[{"id":"10.13039\/501100013314","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>An improved semantic segmentation method based on object contextual representations network (OCRNet) is proposed to accurately identify zucchinis intercropped with sunflowers from unmanned aerial vehicle (UAV) visible images taken over Hetao Irrigation District, Inner Mongolia, China. The proposed method improves on the performance of OCRNet in two respects. First, based on the object region context extraction structure of the OCRNet, a branch that uses the channel attention module was added in parallel to rationally use channel feature maps with different weights and reduce the noise of invalid channel features. Secondly, Lov\u00e1sz-Softmax loss was introduced to improve the accuracy of the object region representation in the OCRNet and optimize the final segmentation result at the object level. We compared the proposed method with extant advanced semantic segmentation methods (PSPNet, DeepLabV3+, DNLNet, and OCRNet) in two test areas to test its effectiveness. The results showed that the proposed method achieved the best semantic segmentation effect in the two test areas. More specifically, our method performed better in processing image details, segmenting field edges, and identifying intercropping fields. The proposed method has significant advantages for crop classification and intercropping recognition based on UAV visible images, and these advantages are more substantive in object-level evaluation metrics (mIoU and intercropping IoU).<\/jats:p>","DOI":"10.3390\/rs13142706","type":"journal-article","created":{"date-parts":[[2021,7,9]],"date-time":"2021-07-09T10:50:38Z","timestamp":1625827838000},"page":"2706","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["Recognizing Zucchinis Intercropped with Sunflowers in UAV Visible Images Using an Improved Method Based on OCRNet"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6461-6259","authenticated-orcid":false,"given":"Shenjin","family":"Huang","sequence":"first","affiliation":[{"name":"College of Mechanical and Electronic Engineering, Northwest A&F University, Xianyang 712100, China"},{"name":"Key Laboratory of Agricultural Internet of Things, Ministry of Agriculture, Xianyang 712100, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenting","family":"Han","sequence":"additional","affiliation":[{"name":"College of Mechanical and Electronic Engineering, Northwest A&F University, Xianyang 712100, China"},{"name":"Key Laboratory of Agricultural Internet of Things, Ministry of Agriculture, Xianyang 712100, China"},{"name":"Institute of Soil and Water Conservation, Northwest A&F University, Xianyang 712100, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haipeng","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Mechanical and Electronic Engineering, Northwest A&F University, Xianyang 712100, China"},{"name":"Key Laboratory of Agricultural Internet of Things, Ministry of Agriculture, Xianyang 712100, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guang","family":"Li","sequence":"additional","affiliation":[{"name":"College of Mechanical and Electronic Engineering, Northwest A&F University, Xianyang 712100, China"},{"name":"Key Laboratory of Agricultural Internet of Things, Ministry of Agriculture, Xianyang 712100, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiandong","family":"Tang","sequence":"additional","affiliation":[{"name":"College of Water Resources and Architectural Engineering, Northwest A&F University, Xianyang 712100, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,7,9]]},"reference":[{"key":"ref_1","first-page":"73","article-title":"Intercropping: Its importance and research needs. 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