Automatic Change Detection of High Resolution Remote Sensing Images Based on Level Set Evolution and Support Vector Machine Classification by YAN Ming, CAO Guo, XIA Meng

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MSHRNet: a multi-scale high-resolution network for land cover classification from high spatial resolution remote sensing images by Fang Chen, Zhihui Ou, Congrong Li, Lei Wang, Bo Yu

“…To address these challenges, we propose the Multi-Scale High-Resolution Network (MSHRNet) for classifying ground objects from high-resolution remote sensing images. …”
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Integrating unsupervised domain adaptation and SAM technologies for image semantic segmentation: a case study on building extraction from high-resolution remote sensing images by Mengyuan Yang, Rui Yang, Min Wang, Haiyan Xu, Gang Xu

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TPL-DA: A Novel Threshold-Free Pseudolabel Learning Framework for Domain Adaptive Semantic Segmentation of High-Resolution Remote Sensing Images by Yan Ren, Jie Long, Xiaowen Gao, Ming Zhang, Guoqing Liu, Nan Su

“…However, most methods highly depend on extensive annotated data, leading to performance deterioration in complex high-resolution remote sensing cross-domain scenes, where variations in image conditions and environments are prevalent. …”
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Dynamic atrous attention and dual branch context fusion for cross scale Building segmentation in high resolution remote sensing imagery by Yaohui Liu, Shuzhe Zhang, Xinkai Wang, Rui Zhai, Hu Jiang, Lingjia Kong

“…Abstract Building segmentation of high-resolution remote sensing images using deep learning effectively reduces labor costs, but still faces the key challenges of effectively modeling cross-scale contextual relationships and preserving fine spatial details. …”
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Multiscale feature tuned trans-DeepLabV3+ based semantic segmentation of aerial images using improved red piranha optimization algorithm by P. Anilkumar, K. Lokesh, A. Naveen Kumar, D. John Pradeep, Y. V. Pavan Kumar, Rammohan Mallipeddi

Subjects: “…High-resolution aerial images…”
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Weighted Feature Fusion Network Based on Large Kernel Convolution and Transformer for Multi-Modal Remote Sensing Image Segmentation by Jianxia Wang, Shaozu Qiu, Jia Cai, Xiaoming Zhang

“…The heterogeneity and complexity of multi-modal data in high-resolution remote sensing images posed a severe challenge to existing cross-modal networks that aim to fuse complementary information of high-resolution optical and elevation data information (DSM) to achieve accurate semantic segmentation. …”
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Mapping the distribution of pine wilt disease based on selected machine learning algorithms and high-resolution Gaofen-2/7 remote sensing by Yifan Wang, Xiaocheng Zhou, Chongcheng Chen, Xiaoqin Wang, Hao Wu, Fanglin Tan, Ruijiao Wu

“…In key counties and cities, High-resolution satellite imagery (GF-2 and GF-7) was used to construct a bi-level scale-set model (BSM) for efficient image segmentation, followed by selection of the best classification algorithm for data extraction. …”
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Early detection of Citrus Huanglongbing by UAV remote sensing based on MGA-UNet by Naibo Ye, Wenyong Mai, Feng Qin, Sen Yuan, Bo Liu, Zaiyuan Li, Conghui Liu, Fanghao Wan, Wanqiang Qian, Zhongzhen Wu, Xi Qiao

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NRWI: a novel spectral index optimized for waterbody extraction from high-resolution GF-2 satellite imagery by Peng Zhang, Shanchuan Guo, Hong Fang, Pengfei Tang, Cong Lin, Hui Yang, Biao Wang, Yanlan Wu

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Swin-FSNet: A Frequency-Aware and Spatially Enhanced Network for Unpaved Road Extraction from UAV Remote Sensing Imagery by Jiwu Guan, Qingzhan Zhao, Wenzhong Tian, Xinxin Yao, Jingyang Li, Wei Li

“…The efficient recognition of unpaved roads from remote sensing (RS) images holds significant value for tasks such as emergency response and route planning in outdoor environments. …”
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Enhancing semantic segmentation of Ecuadorian shrimp ponds through fine-tuned vision transformers and U-Net architectures utilizing open-source remote sensing data by Daniel Jacome, Jianghao Wang, Yong Ge

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TIMA-Net: A Lightweight Remote Sensing Image Change Detection Network Based on Temporal Interaction Enhancement and Multi-Scale Aggregation by Zhijun Zhou, Xuejie Zhang, Xiaoliang Luo, Lvchun Wang, Wei Yu, Shufang Xu, Longbao Wang

“…However, existing deep learning methods often face challenges of high computational complexity and insufficient detail capture, particularly demonstrating limited performance in detecting high-resolution images and complex change regions. To address these issues, this paper proposes a novel network architecture, TIMA-Net, which is designed for efficient remote sensing image change detection. …”
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Semantic Segmentation of Rice Fields in Sub-Meter Satellite Imagery Using an HRNet-CA-Enhanced DeepLabV3+ Framework by Yifan Shao, Pan Pan, Hongxin Zhao, Jiale Li, Guoping Yu, Guomin Zhou, Jianhua Zhang

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Detailed PV Monitor: A Highly Generalized Photovoltaic Panels Segmentation Network Integrating Context-Aware and Deep Feature Reconstruction by Xiaopu Zhang, Huayi Wu, Kunlun Qi, Yuehui Qian, Yongxian Zhang, Ligang Wang, Jianxun Wang

“…These factors significantly impact the generalization ability of deep learning models in large-scale high-resolution remote sensing applications, thereby limiting the effective monitoring and planning of PV power stations. …”
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Automated Semantic Segmentation of Arctic Surface Water Features with Very-High Resolution Satellite X-Band Radar Imagery and U-Net Deep Learning: Segmentation sémantique automatis... by Michael Allan Merchant, Masoud Mahdianpari, Laura Bourgeau-Chavez, Ben DeVries, Aaron Berg

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Framework for Mapping Sublimation Features on Mars’ South Polar Cap Using Object-Based Image Analysis by Racine D. Cleveland, Vincent F. Chevrier, Jason A. Tullis

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A lightweight machine learning-based melt pond extraction scheme for oblique shipborne imagery by Jiaru Zhou, Peng Lu, Xuewei Li, Miao Yu, Hang Zhang, Puzhen Huo, Qingkai Wang, Huawei Shao, Zongxing Li, Zhijun Li

“…High-resolution shipborne optical images can accurately capture the melt ponds on Arctic sea ice surfaces, serving as an important supplement to satellite remote sensing. …”
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Multi-scale eddy identification and analysis based on deep learning method and ocean color data by Meng Hou, Lixing Fang, Kai Wu, Jie Yang, Ge Chen

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MFSM-Net: Multimodal Feature Fusion for the Semantic Segmentation of Urban-Scale Textured 3D Meshes by Xinjie Hao, Jiahui Wang, Wei Leng, Rongting Zhang, Guangyun Zhang

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