DSiam-CnK: A CBAM- and KCF-Enabled Deep Siamese Region Proposal Network for Human Tracking in Dynamic and Occluded Scenes by Xiangpeng Liu, Jianjiao Han, Yulin Peng, Qiao Liang, Kang An, Fengqin He, Yuhua Cheng

“…To tackle these issues, this study enhances the SiamRPN algorithm by integrating the convolutional block attention module (CBAM), which enhances spatial channel attention. …”
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Unlocking Dynamic Subtle Stimuli Tactile Perception: A Deep Learning‐Enhanced Super‐Resolution Tactile Sensor Array with Rapid Response by Shuyao Zhou, Depeng Kong, Mengke Wang, Baocheng Wang, Yuyao Lu, Honghao Lyu, Zhangli Lu, Yong Tao, Kaichen Xu, Geng Yang

“…This significantly hinders robots from executing accurate, time‐sensitive interaction tasks, particularly during dynamic slight‐contact events. Here, a 130 μm‐thick flexible tactile sensor array is designed, with spatial resolution enhanced by a tailored deep learning model, multistage attention‐based adaptive spatial–temporal graph convolutional networks (MS‐AASTGCN), simultaneously achieving a dynamic response of ≈30 ms and a super‐resolution factor of 75.19. …”
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A Data-Driven Multi-Step Flood Inundation Forecast System by Felix Schmid, Jorge Leandro

“…To provide a dynamic inundation map in real-time, we developed a data-driven multi-step inundation forecast system for fluvial flood events. …”
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IT Equipment Automatic Configuration Method Based on Energy Consumption Prediction by CHEN Xiaojiang, HUANG Hongcong, CAI Xuelong, DING Bo

“…Furthermore, these methods cannot dynamically predict energy consumption based on the type of task, which leads to inaccurate predictions. …”
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Hybrid Deep Learning Architecture with Adaptive Feature Fusion for Multi-Stage Alzheimer’s Disease Classification by Ahmad Muhammad, Qi Jin, Osman Elwasila, Yonis Gulzar

“…The adaptive feature fusion layer, a pivotal advancement, facilitates the dynamic integration of features extracted from a ResNet50-based CNN and a vision transformer (ViT). …”
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Attention community discovery model applied to complex network information analysis by Chen Ruiwu, Liang Zeran

“…The model incorporates convolutional neural networks and spectral clustering algorithms to improve the practical application of CDMs. …”
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Efficient and Effective Detection of Repeated Pattern from Fronto-Parallel Images with Unknown Visual Contents by Hong Qu, Yanghong Zhou, P. Y. Mok, Gerhard Flatz, Li Li

“…The new method leverages deep features from a pre-trained Convolutional Neural Network (CNN) to estimate initial repeated pattern sizes and refines them using a dynamic autocorrelation algorithm. …”
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Post-disaster building damage assessment based on gated adaptive multi-scale spatial-frequency fusion network by Bo Yu, Yao Sun, Jiansong Hu, Fang Chen, Lei Wang

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A Novel Lightweight Framework for Non-Contact Broiler Face Identification in Intensive Farming by Bin Gao, Yongmin Guo, Pengshen Zheng, Kaisi Yang, Changxi Chen

“…The Inception-F module employs a dynamic multi-branch design to enhance multi-scale feature extraction, while the C2f-Faster module leverages partial convolution to reduce computational redundancy and parameter count. …”
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Intrusion Detection and Prevention System (IDPS) Model for IIoT Environments Using Hybridized Framework by Manohar Srinivasan, N. C. Senthilkumar

“…This system will include detection and protection security models to keep the network safe from cyberattacks and other strange things happening. Convolutional Neural Networks (CNNs) are used in pattern recognition for the detection and protection models in this research. …”
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Leveraging Deep Learning for Robust Structural Damage Detection and Classification: A Transfer Learning Approach via CNN by Burak Duran, Saeed Eftekhar Azam, Masoud Sanayei

“…Then, this acceleration time-history series was transformed into grayscale images, serving as inputs for a Convolutional Neural Network developed to detect and classify structural damage states. …”
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AirStrum: A virtual guitar using real-time hand gesture recognition and strumming technique by Beulah ARUL, Shashank PANDA, Tushar NAIR

“…Subsequently, a model based on a Convolutional Neural Network (CNN) is trained and validated using the employed dataset to adeptly recognize and classify guitar chords. …”
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Comprehensive Evaluation of Techniques for Intelligent Chatter Detection in Micro-Milling Processes by Guilherme Serpa Sestito, Wesley Angelino De Souza, Alessandro Roger Rodrigues, Maira Martins Da Silva

“…Frictional and regenerative chatter are the most relevant unstable dynamic conditions in micro-milling. Both phenomena promote chatter, affecting the surface finishing and reducing the tool life. …”
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Integrating deep learning and transfer learning: optimizing white blood cells classification in medical educational institutions by M. Hussein, Faten Abd El-Sattar Zahran El-Mougi

“…Leveraging a dataset of 17,092 CellaVision DM96-generated images standardized for clinical relevance, we implement rigorous preprocessing (normalization, resizing) and dynamic augmentation (rotations, flips) to enhance robustness. …”
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Extraction of built-up areas using Sentinel-1 and Sentinel-2 data with automated training data sampling and label noise robust cross-fusion neural networks by Yu Li, Patrick Matgen, Marco Chini

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Automated Parkinson’s Disease Diagnosis Using Decomposition Techniques and Deep Learning for Accurate Gait Analysis by S. Jeba Priya, C. Anand Deva Durai, M. S. P. Subathra, S. Thomas George, Andrew Jeyabose

“…The optimized VMD-1D-CNN combination demonstrated significant potential for accurately diagnosing PD based on gait dynamics. The successful application of these methods highlights the importance of advanced signal processing techniques in improving the detection and management of neurological disorders.…”
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Diel temperature patterns unveiled: High-frequency monitoring and deep learning in Lake Kasumigaura by Senlin Zhu, Ryuichiro Shinohara, Shin–Ichiro S. Matsuzaki, Ayato Kohzu, Mirai Watanabe, Megumi Nakagawa, Fabio Di Nunno, Jiang Sun, Quan Zhou, Francesco Granata

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DMSF-YOLO: A Dynamic Multi-Scale Fusion Method for Maize Tassel Detection in UAV Low-Altitude Remote Sensing Images by Dongbin Liu, Jiandong Fang, Yudong Zhao

“…In the network’s backbone front, conventional convolutions are replaced with conditional parameter convolutions (CondConv) to enhance feature extraction capabilities. …”
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Application of dynamic enhanced scanning with GD-EOB-DTPA MRI based on deep learning algorithm for lesion diagnosis in liver cancer patients by Bo Liu, Jinhua Yang, Yifei Wu, Xi Chen, Xueru Wu

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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

“…This paper introduces a dual-component neural architecture comprising Hierarchical Dynamic Refinement Attention (HiDRA) and Densely Connected Dilated Block (DCDBlock) to address these challenges systematically. …”
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