A novel approach for detecting malicious hosts based on RE-GCN in intranet by Haochen Xu, Xiaoyu Geng, Junrong Liu, Zhigang Lu, Bo Jiang, Yuling Liu

“…Firstly, the network state is unstructured data that dynamically changes in real-time. Secondly, the large amount of normal traffic in the network drowns out the traces generated by malicious behaviors, leading to the problem of category imbalance. …”
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Multi-Function Working Mode Recognition Based on Multi-Feature Joint Learning by Lei Liu, Minghua Wu, Dongyang Cheng, Wei Wang

“…This hybrid model leverages the local convolution operations of the CNN module to extract local characters from radar pulse sequences, capturing the dynamic patterns of radar waveforms across different modes. …”
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A Lightweight and High-Accuracy Model for Pavement Crack Segmentation by Yuhui Yu, Wenjun Xia, Zhangyan Zhao, Bin He

“…To address this challenge, this paper proposes a lightweight, fully convolutional neural network model, enhanced with spatial information. …”
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Quality Judgment of 3D Face Point Cloud Based on Feature Fusion by Gong Gao, Hong Liu, Hongyu Yang

“…Firstly, the 3D point cloud was preprocessed to cut out the face area, and the image obtained from the point cloud and the corresponding 2D plane depth map projection was used as the input. Secondly, Dynamic Graph Convolutional Neural Network (DGCNN) was trained for point cloud learning and ShuffleNet was trained for image learning. …”
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Hybrid CNN–BiLSTM–DNN Approach for Detecting Cybersecurity Threats in IoT Networks by Bright Agbor Agbor, Bliss Utibe-Abasi Stephen, Philip Asuquo, Uduak Onofiok Luke, Victor Anaga

“…This study addresses the limitations of existing IoT threat detection methods, which often struggle with the dynamic nature of IoT environments and the growing complexity of cyberattacks. …”
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CyclicAugment: Optimized Medical Image Analysis via Adaptive Augmentation Intensity by Min-Jun Kim, Jung-Woo Chae, Hyun-Chong Cho

“…To address this issue, this study proposes CyclicAugment, a novel data-augmentation strategy that dynamically adjusts augmentation intensity in a cyclic manner throughout training. …”
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Application of BERT-GCN Model Based on Strong Link Relation Graph in Water Use Enterprise Classification by Junhong Xiang, Baoxian Zheng, Chenkai Cai, Shuiping Yao, Shang Gao

“…The relevant research provides technical and theoretical guidance for the government to carry out dynamic, rapid and accurate management of the water conservancy industry.…”
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Diagnosis of Alzheimer's disease using non-linear features of ERP signals through a hybrid attention-based CNN-LSTM model by Elias Mazrooei Rad, Sayyed Majid Mazinani, Seyyed Ali Zendehbad

“…Biological signals have a dynamic and non-linear nature, and hence nonlinear analysis is important for understanding the signals. …”
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RDM-YOLO: A Lightweight Multi-Scale Model for Real-Time Behavior Recognition of Fourth Instar Silkworms in Sericulture by Jinye Gao, Jun Sun, Xiaohong Wu, Chunxia Dai

“…Methodologically, Res2Net blocks are first integrated into the backbone network to enable hierarchical residual connections, expanding receptive fields and improving multi-scale feature representation. Second, standard convolutional layers are replaced with distribution shifting convolution (DSConv), leveraging dynamic sparsity and quantization mechanisms to reduce computational complexity. …”
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A Novel Swin-Transformer with Multi-Source Information Fusion for Online Cross-Domain Bearing RUL Prediction by Zaimi Xie, Chunmei Mo, Baozhu Jia

“…Additionally, an offline-online swin-transformer with a dynamic weight updating strategy enhances cross-domain feature learning. …”
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DeepTransIDS: Transformer-Based Deep learning Model for Detecting DDoS Attacks on 5G NIDD by Kumar Harshdeep, Konatham Sumalatha, Rohit Mathur

“…The findings confirm the dominance of the Transformer model in real-time intrusion detection in dynamic 5G networks.…”
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Flexi-YOLO: A lightweight method for road crack detection in complex environments. by Jiexiang Yang, Renjie Tian, Zexing Zhou, Xingyue Tan, Pingyang He

“…The DCNv-C2f module is constructed for the transformation and fusion of feature information, allowing the convolutional kernels to adapt to the complex shape characteristics of cracks dynamically. …”
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Intelligent Fault Warning Method for Wind Turbine Gear Transmission System Driven by Digital Twin and Multi-Source Data Fusion by Tiantian Xu, Xuedong Zhang, Wenlei Sun

“…A digital twin system architecture is developed, comprising a high-precision geometric model and a dynamic mechanism model, enabling real-time interaction and data fusion between the physical transmission system and its virtual model. …”
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Risk Prediction of Coal and Gas Outburst Based on Abnormal Gas Concentration in Blasting Driving Face by Liming Qiu, Yujie Peng, Dazhao Song

“…In order to realize dynamic, continuous, and real-time prediction of coal and gas outburst risk in real time in blasting driving face, an outburst risk prediction method based on the characteristics of gas emission after blasting is proposed. …”
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An Intrusion Detection System over the IoT Data Streams Using eXplainable Artificial Intelligence (XAI) by Adel Alabbadi, Fuad Bajaber

“…Three different DL models, i.e., customized 1-D convolutional neural networks (1-D CNNs), deep neural networks (DNNs), and pre-trained model TabNet, are proposed. …”
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Design and development of an efficient RLNet prediction model for deepfake video detection by Varad Bhandarkawthekar, T. M. Navamani, Rishabh Sharma, K. Shyamala

“…While existing methods often focus on spatial features, they may overlook crucial temporal information distinguishing real from fake content and need to investigate several other Convolutional Neural Network architectures on video-based deep fake datasets.MethodsThis study introduces an RLNet deep learning framework that utilizes ResNet and Long Short Term Memory (LSTM) networks for high-precision deepfake video detection. …”
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Leveraging Deep Learning for Fault Detection and Localization in Distributed Systems by Debolina Ghosh, Jay Prakash Singh

“…The dynamic and complex nature of distributed systems makes fault localization extremely difficult, frequently leading to extended outages and higher operating expenses. …”
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The Application of a Marine Weather Data Reconstruction Model Based on Deep Super-Resolution in Ship Route Optimization by Shangfu Li, Junfu Yuan, Zhizheng Wu

“…Firstly, the model uses a convolutional neural network to extract features from wind speed and wave height data. …”
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Deep attributes and decisions fusion for no-reference video quality analysis by Adil Baig

“…We were able to get results by solely employing dynamically pooled deep features and avoiding the use of manually produced features. …”
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Unsupervised anomaly detection of permanent-magnet offshore wind generators through electrical and electromagnetic measurements by A. Dibaj, M. Valavi, A. R. Nejad

“…An unsupervised convolutional autoencoder (CAE) model, trained on simulated signals from the generator in its healthy state, serves for anomaly detection. …”
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