An adaptive dual distillation framework for efficient remaining useful life prediction by Xiang Cheng, Jun Kit Chaw, Shafrida Sahrani, Mei Choo Ang, Saraswathy Shamini Gunasekaran, Moamin A. Mahmoud, Halimah Badioze Zaman, Yanfeng Zhao, Fuchen Ren

“…Soft-target distillation refines predictive distributions to provide robust supervision and our correlation-based feature alignment preserves inter-feature relationships and prevents information loss. …”
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Blockchain enhanced distributed denial of service detection in IoT using deep learning and evolutionary computation by V. V. S. H. Prasad, Swathi Sowmya Bavirthi, C. S. S. Anupama, E. Laxmi Lydia, K. Sathesh Kumar, Khalid Ammar, Mohamad Khairi Ishak

“…Furthermore, data preprocessing utilizes the min-max scaling method to convert input data into a beneficial format. Additionally, feature selection (FS) is performed using the Aquila optimizer (AO) technique to recognize the most relevant features from input data. …”
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Multimodal representations of transfer learning with snake optimization algorithm on bone marrow cell classification using biomedical histopathological images by Khaled Tarmissi, Jamal Alsamri, Mashael Maashi, Mashael M. Asiri, Abdulsamad Ebrahim Yahya, Abdulwhab Alkharashi, Monir Abdullah, Marwa Obayya

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Cross Attention-Based Multi-Scale Convolutional Fusion Network for Hyperspectral and LiDAR Joint Classification by Haimiao Ge, Liguo Wang, Haizhu Pan, Yanzhong Liu, Cheng Li, Dan Lv, Huiyu Ma

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OPTICALS: A Novel Framework for Optimizing Predictive Trading Indicators in Cryptocurrency Using Advanced Learning Simulations by Hasib Shamshad, Fasee Ullah, Syed Adeel Ali Shah, Muhammad Faheem, Beena Shamshad

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Improved convolutional neural network for precise exercise posture recognition and intelligent health indicator prediction by He Chen, Rongchang Fan

“…We propose a multi-scale feature fusion architecture incorporating spatiotemporal attention mechanisms to enhance key point detection precision while maintaining computational efficiency. …”
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Enhancing Structural Health Monitoring of Super-Tall Buildings Using Support Vector Machines, MEMD, and Wavelet Transform by Rouzbeh Doroudi, Seyed Hossein Hosseini Lavasani, Mohsen Shahrouzi, Aref Afshar

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Real-Time Object Detection Model for Electric Power Operation Violation Identification by Xiaoliang Qian, Longxiang Luo, Yang Li, Li Zeng, Zhiwu Chen, Wei Wang, Wei Deng

“…To handle the second challenge, an adaptive combination of local and global features module is proposed to enhance the discriminative ability of features while maintaining computational efficiency, where the local and global features are extracted respectively via 1D convolutions and adaptively combined by using learnable weights. …”
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Advancing Cosmological Parameter Estimation and Hubble Parameter Reconstruction with Long Short-term Memory and Efficient Kolmogorov–Arnold Networks by Jiaxing Cui, Marek Biesiada, Ao Liu, Cuihong Wen, Tonghua Liu, Jieci Wang

“…LSTM networks are employed to extract features from observational data, enabling accurate parameter inference and posterior distribution estimation without relying on solvable likelihood functions. …”
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Research on Lightweight Model of Multi-person Pose Estimation Based on Improved YOLOv8s-Pose by FU Yu, GAO Shuhui

“…Firstly, a lightweight module C2f-GhostNetBottleNeckV2 is introduced into the backbone to replace the original C2f, reducing the number of parameters. This paper also introduces the Non_Local attention mechanism to integrate the position information of human key points in the image into the channel dimension, thereby enhancing the efficiency of feature extraction and mitigating the accuracy degradation issues that often occur after model lightweighting. …”
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Predicting Wind Turbine Blade Tip Deformation With Long Short‐Term Memory (LSTM) Models by Shubham Baisthakur, Breiffni Fitzgerald

“…ABSTRACT Driven by the challenges in measuring blade deformations, this study presents a novel machine learning methodology to predict blade tip deformation using inflow wind data and operational parameters. Using a long short‐term memory (LSTM) model and a novel feature selection approach based on mutual information and recursive feature addition, this study presents a robust framework for multivariate time series prediction. …”
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Semiconductor Wafer Defect Recognition Based on Improved Coordinate Attention Mechanism by Hao He, Yuanjie Wei, Xionghao Lin, Minmin Zhu, Haizhong Zhang

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Real-Time Detection and Instance Segmentation Models for the Growth Stages of <i>Pleurotus pulmonarius</i> for Environmental Control in Mushroom Houses by Can Wang, Xinhui Wu, Zhaoquan Wang, Han Shao, Dapeng Ye, Xiangzeng Kong

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Multi-Scale Attention Fusion Gesture-Recognition Algorithm Based on Strain Sensors by Zhiqiang Zhang, Jun Cai, Xueyu Dai, Hui Xiao

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MAS-YOLOv11: An Improved Underwater Object Detection Algorithm Based on YOLOv11 by Yang Luo, Aiping Wu, Qingqing Fu

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MMYFnet: Multi-Modality YOLO Fusion Network for Object Detection in Remote Sensing Images by Huinan Guo, Congying Sun, Jing Zhang, Wuxia Zhang, Nengshuang Zhang

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MMEFU-Net: A Mamba-Guided Multi-Encoder Fusion U-Net for Tumor Segmentation in CT Images by Renzheng Xue, Zifeng Zhang, Yaxin Zhao, Qing Zhang, Minghui Liang

“…The model achieves superior Dice Similarity Coefficients (DSC) and Intersection over Union (IoU) scores while significantly reducing computational costs. Notably, MMEFU-Net improves the DSC by 2.16% compared to nnU-Net on the LiTS2017 dataset, with a <inline-formula> <tex-math notation="LaTeX">$35\times $ </tex-math></inline-formula> reduction in parameters and a <inline-formula> <tex-math notation="LaTeX">$25\times $ </tex-math></inline-formula> reduction in computational complexity. …”
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Gait-based Parkinson’s disease diagnosis and severity classification using force sensors and machine learning by Navita, Pooja Mittal, Yogesh Kumar Sharma, Anjani Kumar Rai, Sarita Simaiya, Umesh Kumar Lilhore, Vimal Kumar

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A Two-Tiered Bidirectional Atrous Spatial Pyramid Pooling-Based Semantic Segmentation Model for Landslide Classification Using Remote Sensing Images by G. NaliniPriya, E. Laxmi Lydia, Reem Alshenaifi, Radhika Kavuri, Mohamad Khairi Ishak

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MatSwarm: trusted swarm transfer learning driven materials computation for secure big data sharing by Ran Wang, Cheng Xu, Shuhao Zhang, Fangwen Ye, Yusen Tang, Sisui Tang, Hangning Zhang, Wendi Du, Xiaotong Zhang

“…MatSwarm features two key innovations: a swarm transfer learning method with a regularization term to enhance the alignment of local model parameters, and the use of Trusted Execution Environments (TEE) with Intel SGX for heightened security. …”
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