Securing face images in UAV networks using chaos and DNA cryptography approach by Saba Inam, Shamsa Kanwal, Eaman Amin, Omar Cheikhrouhou, Monia Hamdi

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Criminal emotion detection framework using convolutional neural network for public safety by Jay Raval, Nilesh Kumar Jadav, Sudeep Tanwar, Giovanni Pau, Fayez Alqahtani, Amr Tolba

“…We adopted a convolutional neural network (CNN) to get first trained on crime datasets to bifurcate crime and non-crime images. …”
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A Contrastive-Augmented Memory Network for Anti-UAV Tracking in TIR Videos by Ziming Wang, Yuxin Hu, Jianwei Yang, Guangyao Zhou, Fangjian Liu, Yuhan Liu

“…In the first stage, an instance-guided region proposal network (IG-RPN) is employed to calculate the correlation features between the templates and the searching images and further generate candidate proposals. …”
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Atmospheric Turbulence Intensity Image Acquisition Method Based on Convolutional Neural Network by Yuan Mu, Liangping Zhou, Shiyong Shao, Zhiqiang Wang, Pei Tang, Zhiyuan Hu, Liwen Ye

“…By processing the acquired spot image data, the channel attention and spatial attention mechanisms are utilized, and the convolutional neural network learns the interdependence between the channel and space of the feature image and adaptively recalibrates the feature response in terms of the channel to increase the contribution of the foreground spot and suppress the background features. …”
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Hybrid Convolutional Neural Network for Localization of Epileptic Focus Based on iEEG by Linfeng Sui, Xuyang Zhao, Qibin Zhao, Toshihisa Tanaka, Jianting Cao

“…And then, the time-frequency features and feature maps are fused and fed to a 2d convolutional neural network (CNN). …”
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Ensemble learning driven Kolmogorov-Arnold Networks-based Lung Cancer classification. by Abdul Rahaman Wahab Sait, Eid AlBalawi, Ramprasad Nagaraj

“…The extracted features are classified using spline functions, including linear, cubic, and B-spline of Kolmogorov-Arnold Networks (KANs). …”
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A multimodal functional structure-based graph neural network for fatigue detection by Dongrui Gao, Zhihong Zhou, Zongyao Peng, Haokai Zhang, Shihong Liu, Manqing Wang, Hongli Chang

“…The framework employs differential entropy (DE) features extracted from filtered EEG signals and heart rate variability (HRV) features derived from ECG signals as dual input streams, capturing distinct internal–external interaction patterns. …”
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MulGCN: MultiGraph Convolutional Network for Aspect-Level Sentiment Analysis by Huyen Trang Phan, Van Du Nguyen, Ngoc Thanh Nguyen

“…This research proposes a novel sentiment analysis method applied at the aspect level, called multigraph convolutional network (MulGCN), by integrating three GCNs. Unlike previous GCNs, the MulGCN model can simultaneously capture features related to three knowledge: syntax, semantics, and context by combining the dependency parser tree, affective information in SenticNet, and inter-aspect-aware technique. …”
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Research on Creep Constitutive Model for High Temperature Reactor Based on Neural Network by ZHANG Fan, DAI Shoutong

“…The analysis indicates that the optimized creep constitutive model can describe the creep behavior of materials more accurate than either of the creep theory or neural network training model. The model predicts the long-term creep features with an improved accuracy. …”
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EEG-DGRN: dynamic graph representation network for subject-independent ERP detection by Jiabin Zhu, Xuanyu Jin, Yuhang Ming, Wanzeng Kong

“…Existing event-related potential (ERP) detection methods inadequately consider the dynamic connectivity of EEG signals and event response differences between subjects, limiting the discriminability of task-related features.Methods In this article, we propose EEG-DGRN, a dynamic graph representation network designed for subject-independent ERP detection. …”
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Dual-Branch Luminance–Chrominance Attention Network for Hydraulic Concrete Image Enhancement by Zhangjun Peng, Li Li, Chuanhao Chang, Rong Tang, Guoqiang Zheng, Mingfei Wan, Juanping Jiang, Shuai Zhou, Zhenggang Tian, Zhigui Liu

“…However, images taken in complex hydraulic environments often suffer from degraded quality due to low lighting, shadows, and noise, making it difficult to distinguish defects from the background and thereby hindering accurate defect detection and damage evaluation. In this study, following systematic analyses of hydraulic concrete color space characteristics, we propose a Dual-Branch Luminance–Chrominance Attention Network (DBLCANet-HCIE) specifically designed for low-light hydraulic concrete image enhancement. …”
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Transformer-based tokenization for IoT traffic classification across diverse network environments by Firdaus Afifi, Faiz Zaki, Hazim Hanif, Nik Aqil, Nor Badrul Anuar

“…A key innovation is IoT-Tokenize, a custom tokenization pipeline designed to preserve the structural semantics of network flows by converting statistical traffic features into semantically meaningful feature-value pairs. …”
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Low-resolution activity recognition using super-resolution and model ensemble networks by Tinglong Liu, Haiyan Wang

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Harnessing Large Language Models and Deep Neural Networks for Fake News Detection by Eleftheria Papageorgiou, Iraklis Varlamis, Christos Chronis

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Arrhythmia classification based on multi-input convolutional neural network with attention mechanism. by Bin Zheng, Wenbo Luo, Mingming Zhang, Huiyuan Jin

“…While deep learning has advanced automated ECG analysis, challenges remain in accurately classifying arrhythmias due to signal variability, data imbalance, and feature representation limitations. In this work, we propose a novel arrhythmia classification algorithm based on a multi-input convolutional neural network (CNN) enhanced with a Squeeze-and-Excitation (SE) attention mechanism. …”
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Generating context-specific sports training plans by combining generative adversarial networks. by Juquan Tan, Jingwen Chen

“…This study aims to develop a Generative Adversarial Network (GAN)- based framework to create context-specific training plans by integrating numeric attributes (e.g., age, heart rate) and motion features from video data. …”
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Global confidence degree based graph neural network for financial fraud detection by Jiaxun Liu, Yue Tian, Guanjun Liu

“…Graph Neural Networks (GNNs) are widely used in financial fraud detection due to their excellent ability on handling graph-structured financial data and modeling multilayer connections by aggregating information of neighbors. …”
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An Anonymous and Efficient Authentication Scheme with Conditional Privacy Preservation in Internet of Vehicles Networks by Chaeeon Kim, DeokKyu Kwon, Seunghwan Son, Sungjin Yu, Youngho Park

“…To address these security weaknesses, we propose an anonymous and efficient authentication scheme with conditional privacy-preserving capabilities in IoV networks. The proposed scheme can ensure robustness against various security attacks and provide essential security features. …”
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Short Text Classification Based on Enhanced Word Embedding and Hybrid Neural Networks by Cunhe Li, Zian Xie, Haotian Wang

“…To improve the performance of short text classification, this paper proposes a Word2Vec-based enhanced word embedding method and exhibits the design of a dual-channel hybrid neural network architecture to effectively extract semantic features. …”
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A deep multiple self-supervised clustering model based on autoencoder networks by Ling Zhu, Zijin Liu, Guangyu Liu

“…The proposed model effectively integrates the advantages of autoencoder and fuzzy C-Means clustering, performing multi-level clustering evaluations throughout multiple iterations of the autoencoder network training process. …”
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