Multi-attribute bottleneck identification method for hybrid flow shops in panel furniture intelligent manufacturing by Xinyi Yue, Xianqing Xiong, Mei Zhang, Xiutong Xu

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Integrating fast iterative filtering and ensemble neural network structure with attention mechanism for carbon price forecasting by Wang Zhong, Wang Yue, Wang Haoran, Tang Nan, Wang Shuyue

“…The attention mechanism adaptively captures complex features from multiple factors, while the TCN-LSTM efficiently extracts temporal features from the sequences. …”
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Society 5.0: Shaping the future of e-commerce by Arturs Bernovskis, Deniss Sceulovs, Agnis Stibe

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L-ENet: An Ultralightweight SAR Image Detection Network by Yutong Wang, Min Miao, Shiliang Zhu

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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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Precise Spatial Prediction of Rice Seedlings From Large-Scale Airborne Remote Sensing Data Using Optimized Li-YOLOv9 by Jayakrishnan Anandakrishnan, Arun Kumar Sangaiah, Hendri Darmawan, Nguyen Khanh Son, Yi-Bing Lin, Mohammed J. F. Alenazi

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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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True Leaf Area Index Retrieval Using Terrestrial LiDAR for Broadleaf Trees via Novel Multiinclined-Planes Method by Yuyang Guo, Shihua Li, Hao Tang, Ze He

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DMS-OGSTV: A Novel Infrared Small Target Detection Based on Spatial-Temporal Tensor Model by Xiaoling Ge, Weixian Qian, Zipeng Fu

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Regionalization Analysis of Environmental Drivers of CONUS Grazing Land Biomass by Jisung Geba Chang, Feng Gao, Martha C. Anderson, Richard Cirone, Haoteng Zhao

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FIDC-YOLO: Improved YOLO for Detecting Pine Wilt Disease in UAV Remote Sensing Images via Feature Interaction and Dependency Capturing by Zekun Xu, Yipeng Zhou, Shiting Wen, Weipeng Jing

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DEDANet: Mountainous Cropland Extraction From Remote Sensing Imagery With Detail Enhancement and Distance Attenuation by Liang Huang, Zixuan Zhang, You Yu, Bo-Hui Tang

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An Automatic Method for Powerline Extraction From ALS Point Cloud of Powerline Corridors by Di Cao, Cheng Wang, Haibo Liu, Su Zhang, Meng Du, Pu Wang, Sheng Nie, Sijin Cheng

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UAV-FAENet: Frequency-Aware and Attention-Enhanced Network for Remote Sensing Semantic Segmentation of UAV Imagery by Dongbo Zhou, Huan Wang, Shiyan Pang, Di Chen, Huang Yao, Jie Yu

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Infrared Small Target Detection Based on Approximate Background Regularization and Bimodal Slice Based Graph Constraints by Xiaoling Ge, Zipeng Fu, Xuelian Yu, Weixian Qian, Kan Ren, Minjie Wan, Guohua Gu

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Single-Frame Infrared Target Detection Based on Fast Content-Related Modeling by Zipeng Zhang, Xidong Zhao, Wenzheng Wang, Yuqi Han, Chenwei Deng, Zhuokai Li, Linbo Tang

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DFC-Net: Dual-Branch Collaborative Feature Enhancement for Cloud Detection in Remote Sensing Images by Wanting Zhou, Yan Mo, Qiaofeng Ou, Shaowei Bai

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Cross-Temporal Remote Sensing Image Change Captioning: A Manifold Mapping and Bayesian Diffusion Approach for Land Use Monitoring by Qingshan Bai, Xiaohua Wang

“…Furthermore, visual analysis indicates that CTM accurately captures real change regions while significantly suppressing pseudo-changes, maintaining high descriptive accuracy even in complex environments. This study provides an efficient and precise solution for applications such as land use monitoring, environmental monitoring, and disaster response.…”
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Generative Artificial Intelligence for Hyperspectral Sensor Data: A Review by Diaa Addeen Abuhani, Imran Zualkernan, Raghad Aldamani, Mohamed Alshafai

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Enhancing Ground-Based SAR Monitoring With PCA-Based Geometry Transformation for Improved Phase Unwrapping by Matthieu Rebmeister, Andreas Schenk, Stefan Hinz, Frederic Andrian, Maxime Vonie

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