A Dual-Source Deep Learning Model for Mapping Wet Anabranches in Braided Rivers on the Tibetan Plateau by Xiaolu Liu, Xiaoyi Ma, Shuai Qin, Tang Liu, Chenghu Zhou

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PIPNet: A Deep Convolutional Neural Network for Multibaseline InSAR Phase Unwrapping Based on Pure Integer Programming by Hui Liu, Ke Zheng, Changwei Miao, Xuemei Liu, Xianlin Liu, Lin Li, Yongguang Zhang, Longhai Xiong

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Evaluating the Consistency of Radiometric Cross-Calibrated TOA Radiance Products Between Landsat-8 OLI and Landsat-9 OLI2 by Qilong Zhou, Hongzhao Tang, Wei Chen, Chenchao Xiao

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Plug-and-Play Robust Aerial Object Detection Under Hazy Conditions by Wei Wu, Hao Chang, Zhiwen Chen, Zhu Li

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A Mutual Information Constrained Multitask Learning Method for Very High-Resolution Building Segmentation by Yongchuang Wu, Yingchun Wang, Hui Yang, Peng Zhang, Yanlan Wu, Biao Wang

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Deformable Feature Fusion and Accurate Anchors Prediction for Lightweight SAR Ship Detector Based on Dynamic Hierarchical Model Pruning by Yue Guo, Shiqi Chen, Ronghui Zhan, Wei Wang, Jun Zhang

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A Method for Assessing the Lake Trophic Status Using Hyperspectral Reflectance (400–900 nm) Measured Above Water by Nguyen Thi Thu Ha, Pham Quang Vinh, Nguyen Thien Phuong Thao, Pham Ha Linh, Michael Parsons, Nguyen Van Manh

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Fine-Grained Extraction of Coastal Aquaculture Ponds From Remote Sensing Images Using an Edge-Supervised Multi-task Neural Network by Jian Qi, Min Ji, Fengxiang Jin, Jianran Xu, Hanyu Ji, Juan Wang

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NO₂ Air Pollution Trends and Settlement Growth in Megacities by Thilo Erbertseder, Hannes Taubenbock, Thomas Esch, Lorenza Gilardi, Heiko Paeth, Stefan Dech

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Variation of Bi-Directional Reflectance at Multiple Spatial Resolutions Over Different Land Cover Types Using UAV-Based Multiangle Images by Fan Ye, Xiaoning Zhang, Zhengjie Wang, Yifei Wang, Zhaoyang Peng, Tengying Fu, Ziti Jiao, Yanxuan Wu, Yue Wang, Yadong Dong, Hu Zhang, Lei Cui, Anxin Ding

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Enhancing Urban Heat Island Analysis Through Multisensor Data Fusion and GRU-Based Deep Learning Approaches for Climate Modeling by Ning Tang, Muhammad Farhan, Pir Mohammad, M. Abdullah-Al-Wadud, Saddam Hussain, Umair Hamza, Rana Muhammad Zulqarnain, Nazih Yacer Rebouh

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A Constrained Multi-Objective Optimization Algorithm with a Population State Discrimination Model by Shaoyu Zhao, Heming Jia, Yongchao Li, Qian Shi

“…A simple yet effective resource allocation model is incorporated to address the potential computational resource waste associated with dual populations, enhancing the resource utilization. …”
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Comparison of Language Models in Skills Extraction From Vacancies and Resumes by Lyubov Komarova, Vladimir Soloviev, Alexey Kolosov

“…The result of the study is the selection of the best model and the derivation of functions from the summary text, as well as a comparison of the two sets of functions with each other. …”
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Construction on labor education platform based on RuoYi-Cloud by Zhang Jiaming, Zhou Jie, Zhou Beiping

“…Adopting microservice architecture, it realizes user-friendly interface and highly scalable back-end functions, optimizes system response time and resource utilization to ensure efficient system operation, and provides a good foundation for future functionality expansion with system flexibility and scalability. …”
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TOPSIS method-based decision-making model for bipolar quadripartitioned neutrosophic environment by G. Muhiuddin, Mohamed E. Elnair, Satham Hussain S, Durga Nagarajan

“…Criteria such as energy efficiency, environmental impact, cost and resource availability are considered, each characterized by its respective membership function. …”
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Investigating the AGN-neutrino connection with public IceCube data by Kuhlmann Julian, Capel Francesca

“…We present the first application of a newly developed hierarchical Bayesian analysis framework for the detection of point-like sources of high-energy neutrinos. …”
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Feature Extraction and Classification of Power Quality Disturbances Using Optimized Tunable-Q Wavelet Transform and Incremental Support Vector Machine by Indu Sekhar Samanta, Pravat Kumar Rout, Kunjabihari Swain, Satyasis Mishra, Murthy Cherukuri

“…The widespread integration of renewable energy sources (RESs) into power systems using power electronics-based interface devices has led to a substantial rise in power quality (PQ) issues. …”
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Automated Dead Chicken Detection in Poultry Farms Using Knowledge Distillation and Vision Transformers by Ridip Khanal, Wenqin Wu, Joonwhoan Lee

“…A dynamic frame selection strategy optimizes resource usage by adjusting monitoring intervals based on the chickens’ age, ensuring real-time performance in resource-constrained environments. …”
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Genome-wide identification and expression analysis of bHLH gene family revealed their potential roles in abiotic stress response, anthocyanin biosynthesis and trichome formation in... by Guohua Ding, Yanping Shi, Kerui Xie, Hongbin Li, Guanghui Xiao

“…IntroductionLicorice stands out as an exceptional medicinal resource with a long history of application, attributed to its substantial pharmacological potential. …”
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A Dynamic State Cluster-Based Particle Swarm Optimization Algorithm by Zhenya Diao, Fei Yu, Hongrun Wu, Xuewen Xia

“…To address these limitations, this paper introduces a dynamic state cluster-based particle swarm optimization (DSCPSO) algorithm, which employs population phenotypic entropy based on clustering technique. (1) The algorithm provides theoretical splitting points by mathematically analyzing the population into four states: convergence, exploitation, escape, and exploration, enabling more effective parameter adaptive mechanisms. (2) DSCPSO incorporates sinusoidal chaos mapping to dynamically adjust inertia weights, allowing particles to better align with the population’s evolutionary state. (3) During the convergence state, an intelligent particle migration strategy (IPMS) enhances search efficiency within the solution space, preventing unnecessary computational resource consumption. Eventually, comparative analysis with 10 advanced existing algorithms on the CEC2017 and CEC2022 benchmark suites demonstrates that DSCPSO achieves competitive performance across over 70% of the functions, validating the algorithm’s effectiveness and superiority. …”
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