Label semantics and image features aware remote sensing sample retrieval from multi-source datasets for AI-enabled remote sensing monitoring by XingTao Ren, XingTao Ren, Yan Ma, YiXin Zhou, YiXin Zhou

“…Introduction:With the advent of remote sensing (RS) big data, the evolving deep learning (DL) enabled analysis has shown remarkable potential in uncovering intricate features and detecting environmental changes from the vast influx of remote sensing imagery. …”
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Deceptive Cyber-Resilience in PV Grids: Digital Twin-Assisted Optimization Against Cyber-Physical Attacks by Bo Li, Xin Jin, Tingjie Ba, Tingzhe Pan, En Wang, Zhiming Gu

“…A deceptive cyber-defense mechanism is developed using digital twin technology to mislead adversaries, dynamically generating synthetic PV operational data to divert attack focus away from real assets. …”
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Possibilities of using artificial intelligence technologies in the morphological diagnosis of inflammatory bowel diseases (literature review) by E. G. Churilova, A. B. Kazumova, Kh. M. Akhrieva, N. V. Pachuasvili, A. S. Tertychnyy

“…Endocytoscopy and real-time visualization algorithms improve the accuracy of early detection of mucosal dysplasia. …”
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Research on CNC Machine Tool Spindle Fault Diagnosis Method Based on DRSN–GCE Model by Xiaoxu Li, Jiahao Wang, Jianqiang Wang, Jixuan Wang, Jiaming Chen, Xuelian Yu

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AI-Driven Optimization of Blockchain Scalability, Security, and Privacy Protection by Fujiang Yuan, Zihao Zuo, Yang Jiang, Wenzhou Shu, Zhen Tian, Chenxi Ye, Junye Yang, Zebing Mao, Xia Huang, Shaojie Gu, Yanhong Peng

“…Instead of claiming a deep theoretical integration, we focus on how AI methods, such as machine learning and deep learning, have been effectively adopted to optimize blockchain consensus algorithms, improve smart contract vulnerability detection, and enhance privacy-preserving mechanisms like federated learning and differential privacy. …”
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Monitoring and Analyzing Driver Physiological States Based on Automotive Electronic Identification and Multimodal Biometric Recognition Methods by Shengpei Zhou, Nanfeng Zhang, Qin Duan, Xiaosong Liu, Jinchao Xiao, Li Wang, Jingfeng Yang

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ChurnKB: A Generative AI-Enriched Knowledge Base for Customer Churn Feature Engineering by Maryam Shahabikargar, Amin Beheshti, Wathiq Mansoor, Xuyun Zhang, Eu Jin Foo, Alireza Jolfaei, Ambreen Hanif, Nasrin Shabani

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Diagnosis and Management of Sexually Transmitted Infections Using Artificial Intelligence Applications Among Key and General Populations in Sub-Saharan Africa: A Systematic Review... by Claris Siyamayambo, Edith Phalane, Refilwe Nancy Phaswana-Mafuya

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A Novel Equivariant Self-Supervised Vector Network for Three-Dimensional Point Clouds by Kedi Shen, Jieyu Zhao, Min Xie

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A Complementary Dataset of Scalp EEG Recordings Featuring Participants with Alzheimer’s Disease, Frontotemporal Dementia, and Healthy Controls, Obtained from Photostimulation EEG by Aimilia Ntetska, Andreas Miltiadous, Markos G. Tsipouras, Katerina D. Tzimourta, Theodora Afrantou, Panagiotis Ioannidis, Dimitrios G. Tsalikakis, Konstantinos Sakkas, Emmanouil D. Oikonomou, Nikolaos Grigoriadis, Pantelis Angelidis, Nikolaos Giannakeas, Alexandros T. Tzallas

“…Additionally, a fully preprocessed version is included, using EEGLAB-based pipelines that involve filtering, artifact removal, and Independent Component Analysis, preparing the data for machine learning applications. This new dataset enables the study of brain responses to visual stimulation across different cognitive states and supports the development and validation of automated classification algorithms for dementia detection. …”
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Analysis of Minerals Using Handheld Laser-Induced Breakdown Spectroscopy Technology by Naila Mezoued, Cécile Fabre, Jean Cauzid, YongHwi Kim, Marjolène Jatteau

“…Mineral spectra can serve as reference data to (i) identify relevant emission lines and spectral ranges for specific minerals, (ii) be compared to unknown LIBS spectra for mineral identification, or (iii) constitute input data for machine learning algorithms.…”
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Tri-band vehicle and vessel dataset for artificial intelligence research by Yingjian Liu, Gangnian Zhao, Shuzhen Fan, Cheng Fei, Junliang Liu, Zhishuo Zhang, Liqian Wang, Yongfu Li, Xian Zhao, Zhaojun Liu

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An Integrated Mycobacterial CT Imaging Dataset with Multispecies Information by Zhilin Han, Yuyang Zhang, Wenlong Ding, Xiaoting Zhao, Bingzhen Jia, Tingting Liu, Liang Wan, Zhiheng Xing

“…We address this gap by introducing the first comprehensive CT dataset combining 430 NTM and 871 tuberculosis cases, supplemented with clinical parameters including demographics, symptoms, and mycobacterial species data. This resource aims to catalyze AI algorithm development for differential diagnosis, ultimately enhancing precision in NTM management through advanced machine learning applications.…”
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Multimodal sensor dataset for monitoring older adults post lower limb fractures in community settings by Ali Abedi, Charlene H. Chu, Shehroz S. Khan

“…Multimodal sensor platforms that continuously collect data and analyze it using machine learning algorithms can remotely monitor this population and infer health outcomes. …”
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GastroHUN an Endoscopy Dataset of Complete Systematic Screening Protocol for the Stomach by Diego Bravo, Juan Frias, Felipe Vera, Juan Trejos, Carlos Martínez, Martín Gómez, Fabio González, Eduardo Romero

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Dataset of aerial photographs acquired with UAV using a multispectral (green, red and near-infrared) camera for cherry tomato (Solanum lycopersicum var. cerasiforme) monitoringDrya... by Osiris Chávez-Martínez, Sergio Alberto Monjardin-Armenta, Jesús Gabriel Rangel-Peraza, Zuriel Dathan Mora-Felix, Antonio Jesus Sanhouse-García

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SynthSoM: A synthetic intelligent multi-modal sensing-communication dataset for Synesthesia of Machines (SoM) by Xiang Cheng, Ziwei Huang, Yong Yu, Lu Bai, Mingran Sun, Zengrui Han, Ruide Zhang, Sijiang Li

“…The quality of SynthSoM dataset is validated via statistics-based qualitative inspection and evaluation metrics through machine learning (ML) via real-world measurements. The SynthSoM dataset is open-sourced and provides consistent data for cross-comparing SoM-related algorithms.…”
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OCT5k: A dataset of multi-disease and multi-graded annotations for retinal layers by Mustafa Arikan, James Willoughby, Sevim Ongun, Ferenc Sallo, Andrea Montesel, Hend Ahmed, Ahmed Hagag, Marius Book, Henrik Faatz, Maria Vittoria Cicinelli, Amani A. Fawzi, Dominika Podkowinski, Marketa Cilkova, Diana Morais De Almeida, Moussa Zouache, Ganesham Ramsamy, Watjana Lilaonitkul, Adam M. Dubis

“…This dataset improves upon this with multi-grader and multi-disease labels for training machine learning-based algorithms. The proposed dataset covers three subsets of scans (Age-related Macular Degeneration, Diabetic Macular Edema, and healthy) and annotations for two types of tasks (semantic segmentation and object detection). …”
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Advancing cybersecurity and privacy with artificial intelligence: current trends and future research directions by Krishnashree Achuthan, Sasangan Ramanathan, Sethuraman Srinivas, Raghu Raman

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Artificial intelligence, generative artificial intelligence and research integrity: a hybrid systemic review by Khalid H. Arar, Hamit Özen, Gülşah Polat, Selahattin Turan

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