Recent Advances in Deep Learning-Based Spatiotemporal Fusion Methods for Remote Sensing Images by Zilong Lian, Yulin Zhan, Wenhao Zhang, Zhangjie Wang, Wenbo Liu, Xuhan Huang

“…With the development of computer science, deep learning models, such as convolutional neural networks (CNNs), generative adversarial networks (GANs), Transformers, and diffusion models, have recently been introduced into the field of spatiotemporal fusion, resulting in efficient and accurate algorithms. …”
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FEXGBIDS: Federated XGBoost-Based Intrusion Detection System for In-Vehicle Network by Jie Li, Yuanyuan Song, Ming-Gang Zheng, Shuo Zhang, Han Liang

“…We use the BatchCrypt algorithm to batch encrypt first- and second-order gradients to reduce the computational and communication overhead of Paillier homomorphic encryption. …”
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Enhancing liver disease diagnosis with hybrid SMOTE-ENN balanced machine learning models—an empirical analysis of Indian patient liver disease datasets by Ritu Rani, Garima Jaiswal, Nancy, Lipika, Shashi Bhushan, Fasee Ullah, Prabhishek Singh, Manoj Diwakar, Manoj Diwakar

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Benchmarking Federated Few-Shot Learning for Video-Based Action Recognition by Nguyen Anh Tu, Nartay Aikyn, Nursultan Makhanov, Assanali Abu, Kok-Seng Wong, Min-Ho Lee

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Equitable hospital length of stay prediction for patients with learning disabilities and multiple long-term conditions using machine learning by Emeka Abakasanga, Rania Kousovista, Georgina Cosma, Ashley Akbari, Francesco Zaccardi, Navjot Kaur, Navjot Kaur, Danielle Fitt, Gyuchan Thomas Jun, Reza Kiani, Satheesh Gangadharan

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A Kernel Based Neighborhood Discriminant Submanifold Learning for Pattern Classification by Xu Zhao

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An Automated Method Inspired by Taxonomic Classification for Distinguishing Chilean Pelagic Fish Species by Vincenzo Caro Fuentes, Danny Luarte, Ariel Torres, Jorge E. Pezoa, Sebastian E. Godoy, Sergio N. Torres, Mauricio A. Urbina

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Local Pattern Feature Extraction and Ｒecognition Based on Sparse Ｒepresentation by ZHANG Xue-qin, LIN Ke-zheng, LI Ao

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The Role of Artificial Intelligence (AI) in the Future of Forestry Sector Logistics by Leonel J. R. Nunes

“…Methods: This study combines a literature review and case analysis to assess the impact of AI on forestry logistics. Machine Learning algorithms, optimization systems, and monitoring tools based on the Internet of Things (IoT) and computer vision were analyzed to assess impacts in areas such as transportation planning, inventory management, and forest monitoring. …”
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Research Status and Development Trends of Deep Reinforcement Learning in the Intelligent Transformation of Agricultural Machinery by Jiamuyang Zhao, Shuxiang Fan, Baohua Zhang, Aichen Wang, Liyuan Zhang, Qingzhen Zhu

“…Meanwhile, this paper identifies three major challenges facing DRL in agricultural contexts: the difficulty of dynamic path planning in unstructured environments, constraints imposed by edge computing resources on algorithmic real-time performance, and risks to policy reliability and safety under human–machine collaboration conditions. …”
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ILSTMA: Enhancing Accuracy and Speed of Long-Term and Short-Term Memory Architecture by Zongyu Ming, Zimu Wu, Genlang Chen

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System architecture and key technologies of intelligent, safe and efficient mining for rockburst coal seams by Zhigang DENG, Yunpeng LI, Shankun ZHAO, Yin WANG, Shaogang LI, Linghai KONG, Junjun JIANG, Zhenguo SU, Yizhe LI, Kai QIN

“…Secondly, in the digital model, the excavation process of shaft, roadway and working face is simulated according to the mine mining design scheme. …”
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Application of machine learning to stress corrosion cracking risk assessment by Aeshah H. Alamri

“…With the advancement of digital technology and the fourth industrial revolution called Industrial Internet of Things (IIOT), coupled with the availability of computing power and data, advanced analytical tools like artificial intelligence and machine learning bring powerful algorithms for performing advanced corrosion risk assessment. …”
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Rapid in-air ultrasound holography measurement and camera-in-the-loop generation using thermography by Zak Morgan, Youngjun Cho, Sriram Subramanian

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Predicting chronic pain using wearable devices: a scoping review of sensor capabilities, data security, and standards compliance by Johannes C. Ayena, Johannes C. Ayena, Amina Bouayed, Amina Bouayed, Myriam Ben Arous, Myriam Ben Arous, Youssef Ouakrim, Youssef Ouakrim, Karim Loulou, Karim Loulou, Darine Ameyed, Isabelle Savard, Leila El Kamel, Neila Mezghani, Neila Mezghani

“…Random Forest and multilevel models have demonstrated consistent performance, while advanced models like Convolutional Neural Network-Long Short-Term Memory have faced challenges with data quality and computational demands. …”
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Studies of three dimensional stagged-grid finite difference for Z-axis tipper electromagnetic numerical simulation by Yu Wang, Junhao Qu, Tingting Chen, Shaohui Zhou, Yajun Li

“…However, large-scale 3D forward modeling faces computational challenges due to the increase in data volume. …”
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Using Surrogate Models in the Construction of a Pareto-Optimal Positioning Electropneumatic Actuator with Discrete Pneumatic Valves by M. O. Sheykin, S. N. Cherkasskikh, D. V. Shilin, V. V. Fedenkov

“…Sliding control was selected as a control algorithm, which effectively compensated for external disturbances and uncertainties of the system.Results. …”
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DS-AdaptNet: An Efficient Retinal Vessel Segmentation Framework With Adaptive Enhancement and Depthwise Separable Convolutions by Shuting Chen, Chengxi Hong, Hong Jia

“…Medical image segmentation plays a crucial role in diagnosis and treatment planning, yet faces persistent challenges including limited annotated data, boundary ambiguity, and high computational demands that hinder clinical deployment. …”
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AccFIT-IDS: accuracy-based feature inclusion technique for intrusion detection system by C. Rajathi, P. Rukmani

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Intelligent Dynamic Trajectory Planning of UAVs: Addressing Unknown Environments and Intermittent Target Loss by Zhengpeng Yang, Suyu Yan, Chao Ming, Xiaoming Wang

“…Additionally, considering future practical applications, the predictor and planner adopt a parallel optimization and correction algorithm structure to ensure planning accuracy and computational efficiency. …”
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