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However, SOD in RSI faces numerous challenges, including shadow interference, inter-class feature confusion, as well as unclear target edge contours. Therefore, we designed an effective Global Semantic-aware Aggregation Network (GSANet) to aggregate salient information in RSI. GSANet computes the information entropy of different regions, prioritizing areas with high information entropy as potential target regions, thereby achieving precise localization and semantic understanding of salient objects in remote sensing imagery. Specifically, we proposed a Semantic Detail Embedding Module (SDEM), which explores the potential connections among multi-level features, adaptively fusing shallow texture details with deep semantic features, efficiently aggregating the information entropy of salient regions, enhancing information content of salient targets. Additionally, we proposed a Semantic Perception Fusion Module (SPFM) to analyze map relationships between contextual information and local details, enhancing the perceptual capability for salient objects while suppressing irrelevant information entropy, thereby addressing the semantic dilution issue of salient objects during the up-sampling process. The experimental results on two publicly available datasets, ORSSD and EORSSD, demonstrated the outstanding performance of our method. 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Geosci. Remote Sens."},{"key":"ref_2","first-page":"1","article-title":"ASNet: Adaptive Semantic Network Based on Transformer-CNN for Salient Object Detection in Optical Remote Sensing Images","volume":"62","author":"Yan","year":"2024","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"7109","DOI":"10.1109\/TCSVT.2023.3275252","article-title":"Edge and Skeleton Guidance Network for Salient Object Detection in Optical Remote Sensing Images","volume":"33","author":"Gong","year":"2023","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TGRS.2024.3359684","article-title":"ORSI Salient Object Detection via Progressive Semantic Flow and Uncertainty-aware Refinement","volume":"62","author":"Quan","year":"2024","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1109\/MGRS.2021.3063465","article-title":"Change detection from very-high-spatial-resolution optical remote sensing images: Methods, applications, and future directions","volume":"9","author":"Wen","year":"2021","journal-title":"IEEE Geosci. Remote Sens. Mag."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"103921","DOI":"10.1016\/j.landurbplan.2020.103921","article-title":"Remote sensing in urban planning: Contributions towards ecologically sound policies?","volume":"204","author":"Wellmann","year":"2020","journal-title":"Landsc. Urban Plan."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"534","DOI":"10.1109\/TCSVT.2022.3205182","article-title":"A weakly supervised learning framework for salient object detection via hybrid labels","volume":"33","author":"Cong","year":"2022","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"3104","DOI":"10.1109\/TCSVT.2022.3233131","article-title":"Multiple graph affinity interactive network and a variable illumination dataset for RGBT image salient object detection","volume":"33","author":"Song","year":"2022","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"539","DOI":"10.1109\/TCYB.2022.3163152","article-title":"Edge-guided recurrent positioning network for salient object detection in optical remote sensing images","volume":"53","author":"Zhou","year":"2022","journal-title":"IEEE Trans. Cybern."},{"key":"ref_10","first-page":"1","article-title":"ORSI Salient Object Detection via Cross-Scale Interaction and Enlarged Receptive Field","volume":"20","author":"Zheng","year":"2023","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_11","first-page":"1","article-title":"Multi-Content Complementation Network for Salient Object Detection in Optical Remote Sensing Images","volume":"60","author":"Li","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_12","first-page":"1","article-title":"Lightweight Salient Object Detection in Optical Remote-Sensing Images via Semantic Matching and Edge Alignment","volume":"61","author":"Li","year":"2023","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_13","first-page":"1","article-title":"Lightweight Salient Object Detection in Optical Remote Sensing Images via Feature Correlation","volume":"60","author":"Li","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"526","DOI":"10.1109\/TCYB.2022.3162945","article-title":"Adjacent Context Coordination Network for Salient Object Detection in Optical Remote Sensing Images","volume":"53","author":"Li","year":"2023","journal-title":"IEEE Trans. Cybern."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"13680","DOI":"10.1109\/JSEN.2023.3271391","article-title":"Cross-Attention Guided Group Aggregation Network for Cropland Change Detection","volume":"23","author":"Xu","year":"2023","journal-title":"IEEE Sens. J."},{"key":"ref_16","first-page":"1","article-title":"Attention is all you need","volume":"30","author":"Vaswani","year":"2017","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref_17","unstructured":"Dosovitskiy, A., Beyer, L., Kolesnikov, A., Weissenborn, D., Zhai, X., Unterthiner, T., Dehghani, M., Minderer, M., Heigold, G., and Gelly, S. (2020). An image is worth 16 \u00d7 16 words: Transformers for image recognition at scale. arXiv."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Liu, Z., Lin, Y., Cao, Y., Hu, H., Wei, Y., Zhang, Z., Lin, S., and Guo, B. (2021, January 11\u201317). Swin transformer: Hierarchical vision transformer using shifted windows. Proceedings of the IEEE\/CVF International Conference on Computer Vision, Montreal, BC, Canada.","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Wang, W., Xie, E., Li, X., Fan, D.-P., Song, K., Liang, D., Lu, T., Luo, P., and Shao, L. (2021, January 11\u201317). Pyramid vision transformer: A versatile backbone for dense prediction without convolutions. Proceedings of the IEEE\/CVF International Conference on Computer Vision, Montreal, BC, Canada.","DOI":"10.1109\/ICCV48922.2021.00061"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1007\/s41095-022-0274-8","article-title":"Pvt v2: Improved baselines with pyramid vision transformer","volume":"8","author":"Wang","year":"2022","journal-title":"Comput. Vis. Media"},{"key":"ref_21","first-page":"12077","article-title":"SegFormer: Simple and efficient design for semantic segmentation with transformers","volume":"34","author":"Xie","year":"2021","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref_22","first-page":"1","article-title":"Adaptive Spatial Tokenization Transformer for Salient Object Detection in Optical Remote Sensing Images","volume":"61","author":"Gao","year":"2023","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"17733","DOI":"10.1007\/s00521-023-08640-8","article-title":"Transformer guidance dual-stream network for salient object detection in optical remote sensing images","volume":"35","author":"Zhang","year":"2023","journal-title":"Neural Comput. Appl."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"12581","DOI":"10.1109\/TPAMI.2023.3282631","article-title":"Uniformer: Unifying convolution and self-attention for visual recognition","volume":"45","author":"Li","year":"2023","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_25","first-page":"1","article-title":"Hybrid Attention-Aware Transformer Network Collaborative Multiscale Feature Alignment for Building Change Detection","volume":"73","author":"Xu","year":"2024","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Mei, L., Yu, Y., Shen, H., Weng, Y., Liu, Y., Wang, D., Liu, S., Zhou, F., and Lei, C. (2022). Adversarial multiscale feature learning framework for overlapping chromosome segmentation. Entropy, 24.","DOI":"10.3390\/e24040522"},{"key":"ref_27","unstructured":"Peng, Y., Sonka, M., and Chen, D.Z. (2023). U-Net v2: Rethinking the Skip Connections of U-Net for Medical Image Segmentation. arXiv."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Woo, S., Park, J., Lee, J.-Y., and Kweon, I.S. (2018, January 8\u201314). Cbam: Convolutional block attention module. Proceedings of the European Conference on Computer Vision (ECCV), Munich, Germany.","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Maaz, M., Shaker, A., Cholakkal, H., Khan, S., Zamir, S.W., Anwer, R.M., and Shahbaz Khan, F. (2022, January 23\u201327). Edgenext: Efficiently amalgamated cnn-transformer architecture for mobile vision applications. Proceedings of the European Conference on Computer Vision, Tel Aviv, Israel.","DOI":"10.1007\/978-3-031-25082-8_1"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"111658","DOI":"10.1016\/j.knosys.2024.111658","article-title":"GTMFuse: Group-Attention Transformer-Driven Multiscale Dense Feature-Enhanced Network for Infrared and Visible Image Fusion","volume":"293","author":"Mei","year":"2024","journal-title":"Knowl. Based Syst."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"8395","DOI":"10.1109\/JSTARS.2023.3310208","article-title":"Change guiding network: Incorporating change prior to guide change detection in remote sensing imagery","volume":"16","author":"Han","year":"2023","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"9156","DOI":"10.1109\/TGRS.2019.2925070","article-title":"Nested Network With Two-Stream Pyramid for Salient Object Detection in Optical Remote Sensing Images","volume":"57","author":"Li","year":"2019","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1305","DOI":"10.1109\/TIP.2020.3042084","article-title":"Dense attention fluid network for salient object detection in optical remote sensing images","volume":"30","author":"Zhang","year":"2020","journal-title":"IEEE Trans. Image Process."},{"key":"ref_34","first-page":"8026","article-title":"Pytorch: An imperative style, high-performance deep learning library","volume":"32","author":"Paszke","year":"2019","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Fan, D.-P., Cheng, M.-M., Liu, Y., Li, T., and Borji, A. (2017, January 22\u201329). Structure-measure: A new way to evaluate foreground maps. Proceedings of the IEEE International Conference on Computer Vision, Venice, Italy.","DOI":"10.1109\/ICCV.2017.487"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Fan, D.-P., Gong, C., Cao, Y., Ren, B., Cheng, M.-M., and Borji, A. (2018). Enhanced-alignment measure for binary foreground map evaluation. arXiv.","DOI":"10.24963\/ijcai.2018\/97"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Achanta, R., Hemami, S., Estrada, F., and Susstrunk, S. (2009, January 20\u201325). Frequency-tuned salient region detection. Proceedings of the 2009 IEEE Conference on Computer Vision and Pattern Recognition, Miami, FL, USA.","DOI":"10.1109\/CVPRW.2009.5206596"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"3804","DOI":"10.1109\/TIP.2021.3065239","article-title":"SAMNet: Stereoscopically attentive multi-scale network for lightweight salient object detection","volume":"30","author":"Liu","year":"2021","journal-title":"IEEE Trans. Image Process."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"4439","DOI":"10.1109\/TCYB.2020.3035613","article-title":"Lightweight salient object detection via hierarchical visual perception learning","volume":"51","author":"Liu","year":"2020","journal-title":"IEEE Trans. Cybern."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Lin, Y., Sun, H., Liu, N., Bian, Y., Cen, J., and Zhou, H. (2022, January 21\u201325). A lightweight multi-scale context network for salient object detection in optical remote sensing images. Proceedings of the 2022 26th International Conference on Pattern Recognition (ICPR), Montreal, QC, Canada.","DOI":"10.1109\/ICPR56361.2022.9956350"},{"key":"ref_41","first-page":"1","article-title":"ORSI Salient Object Detection via Multiscale Joint Region and Boundary Model","volume":"60","author":"Tu","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_42","first-page":"1","article-title":"Progressive Attention-Based Feature Recovery With Scribble Supervision for Saliency Detection in Optical Remote Sensing Image","volume":"60","author":"Li","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_43","first-page":"1","article-title":"Edge-Aware Multiscale Feature Integration Network for Salient Object Detection in Optical Remote Sensing Images","volume":"60","author":"Zhou","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_44","first-page":"1","article-title":"Adaptive Edge-Aware Semantic Interaction Network for Salient Object Detection in Optical Remote Sensing Images","volume":"61","author":"Zeng","year":"2023","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"5173","DOI":"10.1109\/JSTARS.2024.3365729","article-title":"Adaptive Dual-Stream Sparse Transformer Network for Salient Object Detection in Optical Remote Sensing Images","volume":"17","author":"Zhao","year":"2024","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_46","first-page":"1","article-title":"Hybrid feature aligned network for salient object detection in optical remote sensing imagery","volume":"60","author":"Wang","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"5257","DOI":"10.1109\/TIP.2023.3314285","article-title":"Salient object detection in optical remote sensing images driven by transformer","volume":"32","author":"Li","year":"2023","journal-title":"IEEE Trans. Image Process."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"100596","DOI":"10.1016\/j.cosrev.2023.100596","article-title":"Graph-based deep learning techniques for remote sensing applications: Techniques, taxonomy, and applications\u2014A comprehensive review","volume":"50","author":"Khlifi","year":"2023","journal-title":"Comput. Sci. Rev."}],"container-title":["Entropy"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1099-4300\/26\/6\/445\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T14:48:51Z","timestamp":1760107731000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1099-4300\/26\/6\/445"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,25]]},"references-count":48,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2024,6]]}},"alternative-id":["e26060445"],"URL":"https:\/\/doi.org\/10.3390\/e26060445","relation":{},"ISSN":["1099-4300"],"issn-type":[{"value":"1099-4300","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,5,25]]}}}