Improving Disparity Consistency With Self-Refined Cost Volumes for Deep Learning-Based Satellite Stereo Matching by Jiyong Kim, Seoyeon Cho, Minkyung Chung, Yongil Kim

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AuxTransUNet: Enhancing Remote Sensing Image Segmentation of Open-Pit Mining Areas in Qinghai–Tibet Plateau by Fangzhou Hong, Guojin He, Guizhou Wang, Zhaoming Zhang, Yan Peng

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SGCM: Semantic and Geometric Consistency for Robust Aerial Image Matching by Xiangzeng Liu, Guanglu Shi, Chi Wang, Xiaodong Zhang, Qiguang Miao

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Deep Temporal Joint Clustering for Satellite Image Time-Series Analysis by Wenqi Guo, Zheng Zhang, Yu Meng, Weixiong Zhang, Shichen Gao, Ping Tang

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FloodNet-Lite: A Lightweight Deep Learning for Flood Mapping Using Remote Sensing Data With Optimized UNet and Edge Deployment Approach in 6G by Puviyarasi Thirugnanasammandamoorthi, Debabrata Ghosh, Ram Kishan Dewangan, Mohammad Kamrul Hasan, Khairul Akram Zainol Ariffin, Huda Saleh Abbas, Hashim Elshafie, Rashid A. Saeed, Ala Eldin Awouda

“…However, existing deep-learning (DL) models often face challenges related to computational complexity, latency, and limited scalability in dynamic and resource-constrained environments. …”
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Spatiotemporal Decoupling Between Intensive Policy Interventions and Natural Gradual Recovery in Human–Land Systems During Transition Periods: A Remote Sensing Analysis by Xiao Xie, Chunxiao Zhang, Haojie Kang, Chao E, Jingzhong Li, Wanxia Ren

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Hyperspectral Image Super-Resolution via Grouped Second-Order Spatial Features and Spectral Attention Network by Allen Patnaik, M. K. Bhuyan, Sultan Alfarhood, Mejdl Safran

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Ground-Independent UAV Quantitative Mapping and In Situ Experimental Validation for Coral Reef Habitats by Enze Wang, Huaguo Zhang, Yunhan Ma, Han Tong, Juan Wang, Wenting Cao, Dongling Li

“…Optically shallow waters, which host ecosystems like coral reefs, are characterized by complex radiative transfer pathways. Surface reflectance derived from remote sensing in optically shallow waters is influenced by water depth, water quality, and bottom reflectance. …”
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CFFormer: Channel Fourier Transformer for Remote Sensing Super Resolution by Zexin Xie, Jian Wang, Wei Song, Yanling Du, Huifang Xu, Qinhan Yang

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A Synergistic CNN-DF Method for Landslide Susceptibility Assessment by Jiangang Lu, Yi He, Lifeng Zhang, Qing Zhang, Jiapeng Tang, Tianbao Huo, Yunhao Zhang

“…The complex structures and intricate hyperparameters of existing deep learning (DL) models make achieving higher accuracy in landslide susceptibility assessment (LSA) time-consuming and labor-intensive. …”
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Deep Learning-Based Spatial Prediction of Landslide Risk in Coastal Areas Using GIS and Multicriteria Decision Making: A DeepLabV3+ Approach by Huyong Yan, Asad Khan, Ahsan Jamil, Belkendil Abdeldjalil, Taoufik Saidani, Nazih Y. Rebouh

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Ortho-3DGS: True Digital Orthophoto Generation From Unmanned Aerial Vehicle Imagery Using the Depth-Regulated 3D Gaussian Splatting by Junxing Yang, Zhenglong Cai, Tianjiao Wang, Tong Ye, Haoran Gao, He Huang

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Multiclass Crop Interpretation via a Lightweight Attentive Feature Fusion Network Using Vehicle-View Images by Wenyue Li, Bingfang Wu, Runyu Fan, Fuyou Tian, Miao Zhang, Zhaoying Zhou, Jun Hu, Ruyi Feng, Fangming Wu

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Refinement Analysis of Real Dihedral and Trihedral CR-InSAR Based on TerraSAR-X and Sentinel-1A Images by Hui Liu, Bochen Zhou, Changwei Miao, Shihuan Li, Lei Xu, Ke Zheng, Geshuang Li, Shiji Yang, Mengyuan Zhu

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SHARP-Net: A Refined Pyramid Network for Deficiency Segmentation in Culverts and Sewer Pipes by Rasha Alshawi, Md Meftahul Ferdaus, Md Tamjidul Hoque, Kendall Niles, Ken Pathak, Steve Sloan

“…This article introduces the semantic Haar-adaptive refined pyramid network (SHARP-Net), a novel architecture for semantic segmentation that delivers precise and efficient defect detection. SHARP-Net combines multiscale feature fusion, depthwise separable convolutions, and fine-tuned Haar-like features to enhance performance while reducing computational complexity. …”
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PIDLF+: A Novel Adaptive PIDLF for Forestry Height Mapping Based on Single-Baseline PolInSAR Data by Dandan Li, Hailiang Lu, Mercedes E. Paoletti, Juan M. Haut, Juntao Gu, Chao Li, Weipeng Jing

“…Nevertheless, due to the complex terrain of forest areas, it is difficult to ensure the inversion accuracy when training in a specific forested scene and then applying it to other areas. …”
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Performance Evaluation of Support Vector Machine and Stacked Autoencoder for Hyperspectral Image Analysis by Brahim Jabir, Bendaoud Nadif, Isabel De la Torre Diez, Helena Garay, Irene Delgado Noya

“…When labeled data are scarce, which is a common challenge in remote sensing, SVM proves more reliable and efficient. Conversely, when abundant training data are available, SAE demonstrates impressive capabilities in learning complex patterns. …”
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Automated Creation and Provisioning of Decision Information Packages for the Smart Factory by Eva Hoos, Pascal Hirmer, Bernhard Mitschang

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Research on Cross-Sensor Remote Sensing Image Super-Resolution Method Based on Diffusion Models by Ru Miao, Kai Yang, Ke Zhou, Jia Song, Shihao Fu, Cong Liu, Yuanxing Wang

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Three Decades of Land Cover Dynamics in a Boreal Coastal Basin: A Multisensor Spectral Index and Machine Learning Approach Using Landsat Data and GB-SAR Data by Jinsong Zhang, Bochi Zou, Yifei Yuan, Asad Khan, Muhammad Bilawal Junaid, Qaiser Abbas, Rana Muhammad Zulqarnain, Nazih Y. Rebouh, Olga D. Kucher, Hassan Alzahrani

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