Real-Time Fatigue Detection Algorithms Using Machine Learning for Yawning and Eye State by Fazliddin Makhmudov, Dilmurod Turimov, Munis Xamidov, Fayzullo Nazarov, Young-Im Cho

“…This article gives a complete analysis of a real-time, non-intrusive sleepiness detection system based on convolutional neural networks (CNNs). …”
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Machine learning prediction of permeability distribution in the X field Malay Basin using elastic properties by Zaky Ahmad Riyadi, John Oluwadamilola Olutoki, Maman Hermana, Abdul Halim Abdul Latif, Ida Bagus Suananda Yogi, Said Jadid A. Kadir

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Radar Waveform Recognition With ConvNeXt and Focal Loss by Liping Luo, Jie Huang, Yang Yang, Dexiu Hu

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Computational methods and technical means of processing signals of side electromagnetic emanation by Danil A. Shinyaev, Leonid N. Kessarinskiy, Egor A. Simakhin

“…Due to the 10-bit noise-resistant encoding of video information for digital data transmission interfaces, signal analysis and image restoration are most difficult. …”
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Automatic Correction System for Learning Activities in Remote-Access Laboratories in the Mechatronics Area by Guido S. Machado, Thiago R. M. Salgado, Florindo A. C. Ayres, Iury V. Bessa, Renan L. P. Medeiros, Vicente F. Lucena

“…The application of CNNs serves to validate the results of the experiments through image analysis, whereas generative AI helps to identify patterns. …”
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Computational modelling reveals neurobiological contributions to static and dynamic functional connectivity patterns by Linnea Hoheisel, Linnea Hoheisel, Hannah Hacker, Gereon R Fink, Gereon R Fink, Silvia Daun, Silvia Daun, Joseph Kambeitz, Joseph Kambeitz

“…Recent advances in computational modelling allow us to investigate the relationship of both static FC (sFC) and dynamic FC (dFC) with neurobiology non-invasively.In this study, we modelled the brain activity of 200 healthy individuals based on empirical resting-state functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) data. …”
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Global collaboration and innovation in malignant cerebral edema research: a bibliometric perspective by Xinhua Peng, Xinhua Peng, Rongrong Zhu, Ke Zhang, Jianghong Ji, Chuanguo Lv, Feng Feng, Feng Feng

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Survey on 3D Anomaly Detection Regarding Defect Size: Tradeoff Between Accuracy and Efficiency With Future Research Direction by A-Seong Moon, Kunho Lee, Jaesung Lee

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AI improves consistency in regional brain volumes measured in ultra-low-field MRI and 3T MRI by Kh Tohidul Islam, Shenjun Zhong, Parisa Zakavi, Helen Kavnoudias, Helen Kavnoudias, Shawna Farquharson, Gail Durbridge, Markus Barth, Markus Barth, Andrew Dwyer, Andrew Dwyer, Katie L. McMahon, Paul M. Parizel, Paul M. Parizel, Richard McIntyre, Richard McIntyre, Gary F. Egan, Meng Law, Meng Law, Zhaolin Chen, Zhaolin Chen

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Disrupted topological organization of brain connectome in patients with chronic low back related leg pain and clinical correlations by Yuqi Ji, Xiao Liang, Yixiu Pei, Xiaoying Zuo, Yanyan Zhu, Jie Xu, Qinmei Kuang, Ziwei Yang, Fuqing Zhou, Yong Zhang

“…In this study, we collected resting-state functional and structural magnetic resonance imaging data, along with clinical symptom evaluation data, from 32 cLBLP patients and 31 healthy controls. …”
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Transforming 3D MRI to 2D Feature Maps Using Pre-Trained Models for Diagnosis of Attention Deficit Hyperactivity Disorder by Elahe Hosseini, Seyyed Ali Hosseini, Stijn Servaes, Brandon Hall, Pedro Rosa-Neto, Ali-Reza Moradi, Ajay Kumar, Mir Mohsen Pedram, Sanjeev Chawla

“…Four deep-learning architectures—convolutional neural network 2D (CNN2D), CNN1D, long short-term memory (LSTM), and gated recurrent units (GRU)—were employed for analysis of the MRI data, with and without the inclusion of clinical characteristics. …”
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Transcranial direct current stimulation for patients with walking difficulties caused by cerebral small vessel disease: a randomized controlled study by Qiaoqiao Xu, Qiaoqiao Xu, Wenwen Yin, Xia Zhou, Shuo Wang, Sishi Chen, Jiajia Yang, Chunhua Xi, Zhongwu Sun

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Research on the characteristics of the falling behavior of mixed coal and gangue by SHAN Pengfei, YANG Tong, SUN Haoqiang, XI Bojia

“…Traditional studies on the dynamic characteristics of coal flow during the top coal caving process, based on image detection technology, have primarily focused on specific-stage image analysis, lacking a comprehensive analysis of dynamic characteristics across all stages. …”
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Machine learning and facial recognition for down syndrome detection: A comprehensive review by Khosro Rezaee

“…This paper explores various facial analysis techniques, including deep convolutional neural networks (DCNNs) and hybrid models combining traditional image processing with deep learning. …”
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An automatic classification of breast cancer using fuzzy scoring based ResNet CNN model by Nisha Y., Jagadeesh Gopal

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Abnormal Granger causal connectivity based on altered gray matter volume and associated neurotransmitters of adolescents with internet gaming disorder revealed by a multimodal neur... by Xiaoyu Niu, Mengzhe Zhang, Xinyu Gao, Jinghan Dang, Jieping Sun, Qiuying Tao, Yan Lang, Weijian Wang, Yarui Wei, Shaoqiang Han, Huayan Xu, Yingkun Guo, Jingliang Cheng, Yong Zhang

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Advancements in Plant Protection Technologies and Mechanization in the Russian Federation by A. K. Lysov, T. V. Kornilov

“…Notably, spectrometry is used to create spectral image libraries of cultivated and weedy, healthy and diseased plants, facilitating the automatic decoding of data collected from field through neural networks (artificial intelligence). …”
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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

“…This study focuses on the role of artificial intelligence (AI) in the morphological diagnosis of IBD, endoscopic visualization, outcome prediction, and patient monitoring. Aim: To summarize data on the application of AI methods in the diagnosis and treatment of IBD, including digital image analysis, remission prediction, inflammation activity evaluation, and the automation of histological and endoscopic assessment processes. …”
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Investigating resting-state functional connectivity of the human hand motor system: an offline TMS-fMRI study by Enrica Pierotti, Chiara Speranza, Luigi Cattaneo, Luca Turella

“…Our aim was to better characterize its functional connectivity profiles.We combined offline Transcranial Magnetic Stimulation (TMS) with resting-state functional magnetic resonance imaging (RS-fMRI) to map the changes in functional connectivity following the stimulation of a key node in this network, the human Anterior Intraparietal area (hAIP). …”
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Interpretable and generalizable deep learning model for preoperative assessment of microvascular invasion and outcome in hepatocellular carcinoma based on MRI: a multicenter study by Xue Dong, Xibin Jia, Wei Zhang, Jingxuan Zhang, Hui Xu, Lixue Xu, Caili Ma, Hongjie Hu, Jiawen Luo, Jingfeng Zhang, Zhenchang Wang, Wenbin Ji, Dawei Yang, Zhenghan Yang

“…Biological function analysis was employed to enhance the interpretability and clinical translatability of the adversarial network-based model. …”
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