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By using a hierarchical image segmentation algorithm to predict the boundary map, we select the optimal scale of high-quality hierarchies. In the initialization step, scribble annotations and the saliency map are combined to construct a graphic model over the optimal scale segmentation. By solving the minimal cut problem, it can spread information from scribbles to unmarked regions. In the training process, the segmentation network is trained by using the initial pixel-level annotations. To iteratively optimize the segmentation, we use a graphical model to refine segmentation masks and retrain the segmentation network to get more precise pixel-level annotations. The experimental results on Pascal VOC 2012 dataset demonstrate that the proposed framework outperforms most of weakly supervised semantic segmentation methods and achieves the state-of-the-art performance, which is [Formula: see text] mIoU. <\/jats:p>","DOI":"10.1142\/s0218001421540264","type":"journal-article","created":{"date-parts":[[2021,5,22]],"date-time":"2021-05-22T05:03:46Z","timestamp":1621659826000},"page":"2154026","source":"Crossref","is-referenced-by-count":25,"title":["Optimal Scale of Hierarchical Image Segmentation with Scribbles Guidance for Weakly Supervised Semantic Segmentation"],"prefix":"10.1142","volume":"35","author":[{"given":"Zaid","family":"Al-Huda","sequence":"first","affiliation":[{"name":"School of Computing and Artificial Intelligent, Southwest Jiaotong University, 610031 Chengdu, Sichuan, P.\u00a0R.\u00a0China"}]},{"given":"Donghai","family":"Zhai","sequence":"additional","affiliation":[{"name":"School of Computing and Artificial Intelligent, Southwest Jiaotong University, 610031 Chengdu, Sichuan, P.\u00a0R.\u00a0China"}]},{"given":"Yan","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Computing and Artificial Intelligent, Southwest Jiaotong University, 610031 Chengdu, Sichuan, P.\u00a0R.\u00a0China"}]},{"given":"Riyadh Nazar Ali","family":"Algburi","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Southwest Jiaotong University, 610031 Chengdu, Sichuan, P.\u00a0R.\u00a0China"}]}],"member":"219","published-online":{"date-parts":[[2021,5,21]]},"reference":[{"key":"S0218001421540264BIB001","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2012.120"},{"key":"S0218001421540264BIB002","doi-asserted-by":"publisher","DOI":"10.3390\/en12142816"},{"key":"S0218001421540264BIB003","doi-asserted-by":"publisher","DOI":"10.1109\/NAECON46414.2019.9057822"},{"key":"S0218001421540264BIB005","doi-asserted-by":"publisher","DOI":"10.1109\/ISKE47853.2019.9170333"},{"key":"S0218001421540264BIB006","doi-asserted-by":"publisher","DOI":"10.1049\/ipr2.12020"},{"key":"S0218001421540264BIB007","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2010.161"},{"key":"S0218001421540264BIB008","first-page":"20","volume-title":"Proc. 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