Multi-View Collaborative Training and Self-Supervised Learning for Group Recommendation by Feng Wei, Shuyu Chen

“…We propose MCSS (multi-view collaborative training and self-supervised learning), a novel framework that harnesses both multi-view collaborative training and self-supervised learning specifically for group recommendations. …”
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Turing patterns across geometries: A proven DSC-ETDRK4 solver from plane to sphere by Kolade M. Owolabi, Edson Pindza, Eben Maré

“…This paper presents a unified and robust numerical framework that combines the Discrete Singular Convolution (DSC) method for spatial discretization with the Exponential Time Differencing Runge–Kutta (ETDRK4) scheme for temporal integration to solve reaction–diffusion systems. …”
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Partial feature reparameterization and shallow-level interaction for remote sensing object detection by Minh Tai Pham Nguyen, Quoc Duy Nam Nguyen, Hoang Viet Anh Le, Minh Khue Phan Tran, Tadashi Nakano, Thi Hong Tran

“…Firstly, an extraction block is proposed called PRepConvBlock that leverages reparameterization convolution and partial feature utilization to effectively reduce the complexity in convolution operations, allowing for the utilization of larger kernel sizes in order to form the longer interactions between features and significantly expand receptive fields. …”
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FP-YOLOv8: Surface Defect Detection Algorithm for Brake Pipe Ends Based on Improved YOLOv8n by Ke Rao, Fengxia Zhao, Tianyu Shi

“…This algorithm is developed based on the YOLOv8n framework with the aim of improving accuracy and model lightweight design. …”
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DDI-KGAT: A Graph Attention Network on Biomedical Knowledge Graph for the Prediction of Drug-Drug Interactions by Iqra Naseer Kundi, Shahzad Amin Sheikh, Fahad Mumtaz Malik, Kamran Aziz Bhatti

“…Our study highlights the potential of attention mechanisms in knowledge graph-based drug combination prediction, and we believe that KGAT can serve as a valuable framework for future research in this field.…”
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A systematic review on the associations between built environment and mental health among older people by Yongkang Chen, Lizhen Xu, Xiangfen Cui, Haoran Yang, Haoran Yang, Yiling Liu, Xin Gao, Jianhong Huang

“…We have established a quantifiable evaluation framework for BE elements, addressing the limitations of previous studies that relied on subjective perception measurements. …”
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Deep learning-enabled exploration of global spectral features for photosynthetic capacity estimation by Xianzhi Deng, Xiaolong Hu, Liangsheng Shi, Chenye Su, Jinmin Li, Shuai Du, Shenji Li

“…Our model provides a new framework for interpreting spectral information and accurately estimating photosynthetic capacity.…”
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Self-Supervised Learning of End-to-End 3D LiDAR Odometry for Urban Scene Modeling by Shuting Chen, Zhiyong Wang, Chengxi Hong, Yanwen Sun, Hong Jia, Weiquan Liu

“…To address these challenges, we propose UnMinkLO-Net, an end-to-end self-supervised LiDAR odometry framework. Our method is as follows: (1) we efficiently encode 3D point cloud structures using voxel-based sparse convolution, and (2) we model inherent alignment uncertainty via covariance matrices, enabling novel self-supervised loss based on uncertainty modeling. …”
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Intelligent deep learning architecture for precision vegetable disease detection advancing agricultural new quality productive forces by Jun Liu, Xuewei Wang, Qian Chen, Peng Yan, Dugang Guo

“…To tackle these challenges, this study proposes YOLO-vegetable, a high-precision detection algorithm based on improved You Only Look Once version 10 (YOLOv10). The framework incorporates three innovative modules. The Adaptive Detail Enhancement Convolution (ADEConv) module employs dynamic parameter adjustment to preserve fine-grained features while maintaining computational efficiency. …”
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HiDRA-DCDNet: Dynamic Hierarchical Attention and Multi-Scale Context Fusion for Real-Time Remote Sensing Small-Target Detection by Jiale Wang, Zhe Bai, Ximing Zhang, Yuehong Qiu, Fan Bu, Yuancheng Shao

“…With 8.1 GFLOPs computational complexity and 2.6 ms inference speed per image, our framework demonstrates practical efficacy for real-time remote sensing applications, achieving superior accuracy–efficiency trade-off compared to existing approaches.…”
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YOLOv7scb: A Small-Target Object Detection Method for Fire Smoke Inspection by Dan Shao, Yu Liu, Guoxing Liu, Ning Wang, Pu Chen, Jiaxun Yu, Guangmin Liang

“…This approach incorporates two key improvements to the YOLOv7 framework: the use of space-to-depth convolution (SPD-Conv) and C3 modules, enhancing the model’s ability to extract features from small targets effectively. …”
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Securing Industrial IoT Environments: A Fuzzy Graph Attention Network for Robust Intrusion Detection by Safa Ben Atitallah, Maha Driss, Wadii Boulila, Anis Koubaa

“…To address these limitations, we propose the Fuzzy Graph Attention Network (FGATN), a novel intrusion detection framework that fuses fuzzy logic, graph attention mechanisms, and GNNs to deliver high accuracy and robustness in IIoT environments. …”
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BDSER-InceptionNet: A Novel Method for Near-Infrared Spectroscopy Model Transfer Based on Deep Learning and Balanced Distribution Adaptation by Jianghai Chen, Jie Ling, Nana Lei, Lingqiao Li

“…To address these limitations, this study proposes a novel transfer learning framework integrating multi-scale network architecture with Balanced Distribution Adaptation (BDA) to enhance cross-instrument compatibility. …”
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ECOLOGICAL RESILIENCE ASSESSMENT FEATURES OF NATURAL-INDUSTRIAL SYSTEMS BY INDEX-BASED METHODS USING SOFT COMPUTING by A.V. Masloboev

“…The unified methodological framework of our study includes the fundamentals of safety sciences, risk management methodology, and the stateof- the-art resilience concept of complex systems, as currently developing research area. …”

Multi-Scale Feature Mixed Attention Network for Cloud and Snow Segmentation in Remote Sensing Images by Liling Zhao, Junyu Chen, Zichen Liao, Feng Shi

“…This work proposes a Multi-scale Feature Mixed Attention Network (MFMANet). The framework integrates three key components: (1) a Multi-scale Pooling Feature Perception Module to capture multi-level structural features, (2) a Bilateral Feature Mixed Attention Module that enhances boundary detection through spatial-channel attention, and (3) a Multi-scale Feature Convolution Fusion Module to reduce edge blurring. …”
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Predicting the Imbalanced Impact of Drugs on Microbial Abundance Using Multi-View Learning and Data Augmentation by Bei Zhu, Haoyang Yu, Bingxue Du, Hui Yu, Jianyu Shi

“…To address these issues, we propose a framework for predicting the imbalanced Impact of Drugs on Microbial Abundance by leveraging Multi-view Learning and Data Augmentation, named IDMA-MLDA. …”
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YOLOv8n-DSDL: A lightweight dual-backbone network with decoupled self-attention for cotton maturity detection by Meiqi Zhong, Linjing Wei, Henghui Mo

“…A novel Decoupled Focused Self-Attention (DFSA) mechanism is designed, which utilizes one-dimensional dilated convolutions and key-value fusion operations to dynamically enhance feature associations and improve perception of subtle visual cues such as color variation and micro-cracks. …”
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High-Precision Pose Measurement of Containers on the Transfer Platform of the Dual-Trolley Quayside Container Crane Based on Machine Vision by Jiaqi Wang, Mengjie He, Yujie Zhang, Zhiwei Zhang, Octavian Postolache, Chao Mi

“…A multi-scale adaptive frequency object-detection framework is developed based on YOLO11, achieving improved detection accuracy for multi-scale lockhole keypoints in perspective-distortion scenarios (mAP@0.5 reaches 95.1%, 4.7% higher than baseline models) through dynamic balancing of high–low-frequency features and adaptive convolution kernel adjustments. …”
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LWSARDet: A Lightweight SAR Small Ship Target Detection Network Based on a Position–Morphology Matching Mechanism by Yuliang Zhao, Yang Du, Qiutong Wang, Changhe Li, Yan Miao, Tengfei Wang, Xiangyu Song

“…On the other hand, to reduce feature dilution and computational redundancy in traditional detection heads when focusing on small targets, we replace conventional convolutions with simple linear transformations and design a lightweight detection head, LSD-Head. …”
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High‐order multilayer attention fusion network for 3D object detection by Baowen Zhang, Yongyong Zhao, Chengzhi Su, Guohua Cao

“…To enhance the expressive power between different modality features, we introduce a high‐order feature fusion module that performs multi‐level convolution operations on the element‐wise summed features. …”
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