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To enhance the shallow semantic information, the efficient and lightweight Normalization-based Attention Module (NAM) is added to capture the feature information of small target objects. The results show that, under the INRIA Aerial Image Dataset and same parameter setting, the Mean Pixel Accuracy (MPA) and Mean Intersection over Union (MIoU) are generally best than DeepLabv3+\u2009, U-Net, and PSP-Net, which are respectively improved by 1.22%, \u2212\u00a00.22%, and 2.22% and 2.17%, 1.35%, and 3.42%. Our proposed method has also a good performance on the small object segmentation and multi-object segmentation. What\u2019s more, it significantly converges faster with fewer model parameters and stronger computing power while ensuring the segmentation effect. It is proved to be robust and can provide a methodological reference for high-precision remote-sensing image semantic segmentation.<\/jats:p>","DOI":"10.1007\/s40747-023-01304-z","type":"journal-article","created":{"date-parts":[[2023,12,15]],"date-time":"2023-12-15T08:02:15Z","timestamp":1702627335000},"page":"2839-2849","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":43,"title":["An improved DeepLabv3+\u2009lightweight network for remote-sensing image semantic segmentation"],"prefix":"10.1007","volume":"10","author":[{"given":"Hui","family":"Chen","sequence":"first","affiliation":[]},{"given":"Yuanshou","family":"Qin","sequence":"additional","affiliation":[]},{"given":"Xinyuan","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Haitao","family":"Wang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8352-7689","authenticated-orcid":false,"given":"Jinling","family":"Zhao","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,12,15]]},"reference":[{"issue":"3\u20134","key":"1304_CR1","first-page":"167","volume":"6","author":"G Huadong","year":"2005","unstructured":"Huadong G, Changlin W (2005) Building up national Earth observing system in China. 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