Roof Geometrical Component Extraction Using Bimodal Data and Graph Neural Network by F. Soleimani Vostikolaei, S. Jabari

“…The proposed approach uses convolutional neural networks (CNNs) to extract roof features from both RGB and DSM data. …”
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A Comprehensive Analysis of Security Challenges in ZigBee 3.0 Networks by Akbar Ghobakhlou, Duaa Zuhair Al-Hamid, Sara Zandi, James Cato

“…While ZigBee 3.0 introduces enhanced security features such as install codes and trust centre link key updates, there remains a lack of empirical research evaluating their effectiveness in real-world deployments. …”
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Siamese network with squeeze-attention for incomplete multi-view multi-label classification by Mengqing Wang, Jiarui Chen, Lian Zhao, Yinghao Ye, Xiaohuan Lu

“…To address these challenges, we propose a model based on a Siamese network with squeeze attention (SSA) for incomplete multi-view multi-label classification (iMvMLC). …”
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Wind Turbine Fault Detection Through Autoencoder-Based Neural Network and FMSA by Welker Facchini Nogueira, Arthur Henrique de Andrade Melani, Gilberto Francisco Martha de Souza

“…The framework integrates autoencoder-based neural networks with Failure Mode and Symptoms Analysis, leveraging the strengths of both methodologies to enhance anomaly detection, feature selection, and fault localization. …”
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Adaptive multi-scale phase-aware fusion network for EEG seizure recognition by Yanting Liang, Jingyuan Liu, Xinzhou Zhang

“…However, traditional methods rely heavily on manual feature extraction, and current deep learning-based approaches still face challenges in frequency adaptability, multi-scale feature integration, and phase alignment.MethodsTo address these limitations, we propose an Adaptive Multi-Scale Phase-Aware Fusion Network (AMS-PAFN). …”
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An attention-enhanced few-shot model for event detection in online social networks by Sielvie Sharma, Tanvir Ahmad, Niyaz Ahmad Wani, Naveed Ahmad, Sadique Ahmad

“…This operation emphasizes pivotal dimensions within the feature space while addressing data sparsity. AttendFew is evaluated on real-world datasets and exhibits significantly better performance than state-of-the-art (SOTA) and other baseline methods in terms of accuracy, F1-score. …”
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TFDense-GAN: a generative adversarial network for single-channel speech enhancement by Haoxiang Chen, Jinxiu Zhang, Yaogang Fu, Xintong Zhou, Ruilong Wang, Yanyan Xu, Dengfeng Ke

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EHO-Q-LGAN: An EHO-Based Q-Learning GAN for the Timely Diagnosis of Diabetic Retinopathy by Maneesha Vadduri, P. Kuppusamy

“…The proposed approach was evaluated on the EyePACS dataset and achieved efficient results in the context of accuracy, sensitivity, and specificity levels. …”
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Mandarin speech reconstruction from surface electromyography based on generative adversarial networks by Fengji Li, Fei Shen, Ding Ma, Jie Zhou, Li Wang, Fan Fan, Tao Liu, Xiaohong Chen, Tomoki Toda, Haijun Niu

“…A speech reconstruction model for Mandarin speech, based on multi-scale feature extraction from EMG and a generative adversarial network (GAN), was developed. …”
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Artificial intelligence-based prescription of personalized scalp cosmetics improved the scalp condition: efficacy results from 100 participants by Bo Ri Kim, Min Jae Kim, Jieun Koo, Hwa-Jung Choi, Kyung Ho Paik, Soon Hyo Kwon, Hye-Ryung Choi, Chang Hun Huh, Jung Won Shin, Dong-sun Park, Jung-Im Na

“…However, it requires trained evaluators.Aim: To develop artificial intelligence (AI) algorithms for assessment of scalp conditions and to assess the feasibility of AI-based recommendations on personalized scalp cosmetics.Methods: Using EfficientNet, convolutional neural network (CNN) models (SPI-AI) ofeach scalp feature were established. 101,027 magnified scalp images graded according to the SPI scoring were used for training, validation, and testing the model Adults with scalp discomfort were prescribed shampoos and scalp serums personalized according to their SPI-AI-defined scalp types. …”
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Distinct functional cerebral hypersensitivity networks during incisional and inflammatory pain in rats by Silke Kreitz, Bruno Pradier, Daniel Segelcke, Saeedeh Amirmohseni, Andreas Hess, Cornelius Faber, Esther M. Pogatzki-Zahn

“…Additionally, we have identified unique Network Signatures of Pain Hypersensitivity (NSPH) for INC and CFA. …”
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Prediction of the onset of the RSV epidemic with meteorological data using deep neural networks by Kazuo Yonekura, Miya Nishio, Momoko Kashiwado, Takuya Naruto, Masaaki Mori

“…Machine learning models including a support vector machine (SVM), XGBoost, and a deep neural network (DNN) were evaluated. Results: The DNN outperformed other models, achieving the highest F1 score (0.71) and recall (0.83), particularly with a 3-week-ahead prediction horizon. …”
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VHR Multispectral Satellite Image Classification with Kolmogorov-Arnold Networks for Urban Applications by M. Fawzy, M. Fawzy, Á. Barsi

“…Additionally, KAN is benchmarked against other methods like traditional Shallow Neural Networks (SNNs). Obtained KAN classification accuracy and computational efficiency are evaluated compared to SNN, highlighting its strengths in modelling complexity with optimized key model parameters. …”
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Precedent phenomena in online blog posts by Drevoten, Ekaterina Александровна

“…Precedent units, possessing the features of recognition, evaluativeness, expressivity, hypertextuality, expand and deepen the semantic content of the genre under study, contribute to the realization of the main task of the online post – attracting and retaining the attention of the audience – and serve as one of the important means of textual organization of this genre. …”
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ANN-SVM-IP: An Innovative Method for Rapidly and Efficiently Detecting and Classifying of External Defects of Apple Fruits by Nashaat M. Hussain Hassan, Mohamed M. Hassan Mahmoud, Mohamed A. Ismeil, M. Mourad Mabrook, A. A. Donkol, A. M. Mabrouk

“…To ensure the reliability of the results obtained, all the techniques used in the trading were evaluated using several different evaluation mechanisms, including accuracy, precision, recall, F1-score, confusion matrix, and runtime analysis. …”
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Predicting Atrial Fibrillation Relapse Using Bayesian Networks: Explainable AI Approach by João Miguel Alves, Daniel Matos, Tiago Martins, Diogo Cavaco, Pedro Carmo, Pedro Galvão, Francisco Moscoso Costa, Francisco Morgado, António Miguel Ferreira, Pedro Freitas, Cláudia Camila Dias, Pedro Pereira Rodrigues, Pedro Adragão

“…ObjectiveThis study aims to investigate the effectiveness of Bayesian networks as a predictive tool for AF relapse following a percutaneous pulmonary vein isolation (PVI) procedure. …”
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HIV disclosure in the social networks of adolescents with HIV in Cape Town, South Africa by Marta I. Mulawa, Marta I. Mulawa, Frances Hung, Nicole J. Phillips, Nicole J. Phillips, Mark F. Austin, Richard Barfield, Hui-Jie Lee, Heather J. Zar, Heather J. Zar, Dan J. Stein, Dan J. Stein, Dan J. Stein, Jacqueline Hoare, Jacqueline Hoare

“…Associations between HIV disclosure and characteristics of APHIV (egos), their relationship to network members (alters), and features of the social network, including ego's network size and alter's centrality within the network, were also examined.MethodsNetwork data were collected from 58 APHIV (mean age 14.3 years; 52% female) using a customized touchscreen-based assessment, providing data on 349 ego-alter relationships. …”
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Simple Yet Powerful: Machine Learning-Based IoT Intrusion System With Smart Preprocessing and Feature Generation Rivals Deep Learning by Kazim Kivanc Eren, Kerem Kucuk, Fatih Ozyurt, Omar H. Alhazmi

“…We evaluated our method on the ToN-IoT dataset, which contains various network traffic data sets and various types of attacks. …”
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Depression detection based on dual path DCGAN data generation and classification-regression network by LU Jingxue, LI Hongyan, ZHENG Ruichao, QIN Ruizhen

“…By constructing a DP-DCGAN network, the feature maps of each depression score in the original dataset were enhanced to increase the diversity of the feature maps, and evaluation indicators were proposed to screen out high-quality feature maps from both spatial characteristics and frequency domain characteristics. …”
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Group Authentication Key Agreement Protocol Based on Certificateless Cryptography in UAV Network by Yuecheng WANG, Youwen ZHU, Zhiqiang ZHANG

“…Therefore, group key agreement protocols for UAV networks must provide a lighter computing process and stronger security guarantees.Methods This protocol adopts a certificateless key system. …”
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