Privacy-sensitive federated learning for cross-domain adaptation: The Mamba-MoE approach by Muhammad Kashif Jabbar, Huang Jianjun, Ayesha Jabbar, Zaka Ur Rehman

“…Conventional approaches, such as Domain-Adversarial Neural Networks (DANN) and Maximum Mean Discrepancy (MMD), rely on large datasets and centralized processing, making them impractical for federated learning due to privacy and computational constraints. …”
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Adversarial denoising of EEG signals: a comparative analysis of standard GAN and WGAN-GP approaches by Imad Eddine Tibermacine, Samuele Russo, Francesco Citeroni, Giuseppe Mancini, Abdelaziz Rabehi, Amal H. Alharbi, El-Sayed M. El-kenawy, El-Sayed M. El-kenawy, Christian Napoli, Christian Napoli, Christian Napoli

“…IntroductionElectroencephalography (EEG) signals frequently contain substantial noise and interference, which can obscure clinically and scientifically relevant features. Traditional denoising approaches, such as linear filtering or wavelet thresholding, often struggle with nonlinear or time-varying artifacts. …”
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Improving Malaria diagnosis through interpretable customized CNNs architectures by Md. Faysal Ahamed, Md Nahiduzzaman, Golam Mahmud, Fariya Bintay Shafi, Mohamed Arselene Ayari, Amith Khandakar, M. Abdullah-Al-Wadud, S. M. Riazul Islam

“…To address these challenges, we employed several customized convolutional neural networks (CNNs), including Parallel convolutional neural network (PCNN), Soft Attention Parallel Convolutional Neural Networks (SPCNN), and Soft Attention after Functional Block Parallel Convolutional Neural Networks (SFPCNN), to improve the effectiveness of malaria diagnosis. …”
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Evaluation of Peroxide Value and Free Fatty Acid Content in Coconut Oil and Palm Oil under Different Heating Temperature Treatments using Reflectance–Fluorescence-based computer vi... by Luluk Oktaviana, Wahyunanto Agung Nugroho, Dimas Firmanda Al Riza Al Riza

“…A classification model was developed using a Convolutional Neural Network (CNN) algorithm to automatically extract color features contributing to oil quality classification. …”
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Estimation of Fractal Dimensions and Classification of Plant Disease with Complex Backgrounds by Muhammad Hamza Tariq, Haseeb Sultan, Rehan Akram, Seung Gu Kim, Jung Soo Kim, Muhammad Usman, Hafiz Ali Hamza Gondal, Juwon Seo, Yong Ho Lee, Kang Ryoung Park

“…RCA-Net leverages attention mechanisms and multiscale feature extraction strategies to enhance salient features while reducing background noises. …”
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Experience of «USPU» in Organization of School and University Partnerships in Training Teachers (Basic Professional Educational Program «Teacher of Primary General Education») by Voronina L.V., Byvsheva M.V.

“…The requirements for the selection of general education organizations as network partners have been singled out. The forms of interaction of all participants of the practice, positively evaluated by students, teachers-instructors, and methodologists of the university are revealed. …”
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Multi-Faceted Adaptive Token Pruning for Efficient Remote Sensing Image Segmentation by Chuge Zhang, Jian Yao

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STATE PREDICTION OF WIND TURBINE GENERATOR BASED ON K-CNN AND N-GRU (MT) by CHAI Tong, YUAN YiPing, MA JunYan, FAN PanPan

“…The feature extraction results after dimensionality reduction were input into N-GRU for prediction and reconstruction error was obtained, then the state evaluation was realized by setting the alarm threshold. …”
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DETECTION OF KERATOCONUS DISEASE DEPENDING ON CORNEAL TOPOGRAPHY USING DEEP LEARNING by Aseel Abdulhasan Hashim, Mahdi Mazinani

“…The pre-processed data is then fed into Machine Learning(ML) algorithms and Convolutional Neural Network(CNN) models, by which the four corneal maps were analyzed. …”
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E-FCNN Based Electric Power Inspection Image Enhancement by Wanrong BAI, Xun ZHANG, Xiaoqin ZHU, Jixiang LIU, Qiyu CHENG, Yan ZHAO, Jie SHAO

“…In order to solve this problem, we propose an edge-aware feedback convolutional neural network (E-FCNN), which not only adds Resnet blocks and feedback mechanism to the conventional super-resolution network to strengthen the ability of feature extraction, but also adds texture information to the edge-aware branch to enhance the image detail. …”
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A Study of Deep Learning Models for Audio Classification of Infant Crying in a Baby Monitoring System by Denisa Maria Herlea, Bogdan Iancu, Eugen-Richard Ardelean

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Handling data sparsity via item metadata embedding into deep collaborative recommender system by Gopal Behera, Neeta Nain

“…The model consists of two stages, wherein the first stage, a neural network, is used to retrieve the data’s nonlinear features through embedding vectors. …”
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Pears Internal Quality Inspection Based on X-Ray Imaging and Multi-Criteria Decision Fusion Model by Zeqing Yang, Jiahui Zhang, Zhimeng Li, Ning Hu, Zhengpan Qi

“…The proposed method combines manual feature-based classifiers, including Local Binary Pattern (LBP) and Histogram of Oriented Gradients (HOG), with a deep convolutional neural network (DCNN) model within an MCD-based fusion framework. …”
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End-Edge Collaborative Lightweight Secure Federated Learning for Anomaly Detection of Wireless Industrial Control Systems by Chi Xu, Xinyi Du, Lin Li, Xinchun Li, Haibin Yu

“…Specifically, we first design a residual multihead self-attention convolutional neural network for local feature learning, where the variability and dependence of spatial-temporal features can be sufficiently evaluated. …”
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SGCM: Semantic and Geometric Consistency for Robust Aerial Image Matching by Xiangzeng Liu, Guanglu Shi, Chi Wang, Xiaodong Zhang, Qiguang Miao

“…To achieve accurate region matching, we construct the region description graphs that incorporate both semantic categories and geometric attributes information. A graph neural network (GNN) is then employed for feature aggregation and node descriptor updates, leading to more robust region representations. …”
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Urban Fire Spatial–Temporal Prediction Based on Multi-Source Data Fusion by Haiyu Xiang, Lizhi Wu, Zidong Guo, Shaoyun Ren

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Dynamical opinion clusters exploration suite: Modeling social media opinion dynamics by Henrique Ferraz de Arruda, Kleber Andrade Oliveira, Yamir Moreno

“…To address the challenges posed by the multifaceted and multidisciplinary nature of this research, coupled with the recent scarcity of data, computational simulation has emerged as a key tool for understanding opinion dynamics in social networks. This paper presents a Python library, DOCES, designed to simulate essential features of real-world social networks. …”
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Research on Shale Oil Well Productivity Prediction Model Based on CNN-BiGRU Algorithm by Yuan Pan, Xuewei Liu, Fuchun Tian, Liyong Yang, Xiaoting Gou, Yunpeng Jia, Quan Wang, Yingxi Zhang

“…The CNN-BiGRU model was implemented on the TensorFlow framework, with rigorous validation of model robustness and systematic evaluation of feature importance. Hyperparameter optimization via grid searching yielded optimal configurations, while field applications demonstrated operational feasibility. …”
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CVT-HNet: a fusion model for recognizing perianal fistulizing Crohn’s disease based on CNN and ViT by Lanlan Li, Ziyue Wang, Chongyang Wang, Tao Chen, Ke Deng, Hong’an Wei, Dabiao Wang, Juan Li, Heng Zhang

“…Convolutional neural networks(CNNs) are the main basis for detecting anal fistulas in current computer vision techniques. …”
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A New Efficient Hybrid Technique for Human Action Recognition Using 2D Conv-RBM and LSTM with Optimized Frame Selection by Majid Joudaki, Mehdi Imani, Hamid R. Arabnia

“…While deep learning models such as 3D convolutional neural networks (CNNs) and recurrent neural networks (RNNs) deliver promising results, they often struggle with computational inefficiencies and inadequate spatial–temporal feature extraction, hindering scalability to larger datasets or high-resolution videos. …”
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