ANALYSIS OF EMOTION RECOGNITION BASED ON DEEP CONVOLUTIONAL NEURAL NETWORK MODELS by V. M. Goryaev, G. A. Mankaeva, T. B. Ochir-Goryaeva, A. B. Mantusov, V. V. Lidji-Garyaev, A. B. Kornyakov

“…Interest in facial emotion recognition is increasing and new algorithms and methods are being introduced. Recent advances in supervised and unsupervised machine learning have led to breakthroughs in research, and more and more accurate systems are emerging every year. …”
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A Distributed RF Threat Sensing Architecture by Georgios Michalis, Andreas Rousias, Loizos Kanaris, Akis Kokkinis , Pantelis Kanaris , Stavros Stavrou

“…The incorporation of the centralized SOC in the overall architecture allows also the centralized application of machine learning algorithms on all the received data.…”
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A Comparative Study of YOLO, SSD, Faster R-CNN, and More for Optimized Eye-Gaze Writing by Walid Abdallah Shobaki, Mariofanna Milanova

“…Using this dataset, we evaluated the performance of several computer vision algorithms across three key areas. For object detection, we implemented YOLOv8, SSD, and Faster R-CNN. …”
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Scalable quality control on processing of large diffusion-weighted and structural magnetic resonance imaging datasets. by Michael E Kim, Chenyu Gao, Nancy R Newlin, Gaurav Rudravaram, Aravind R Krishnan, Karthik Ramadass, Praitayini Kanakaraj, Kurt G Schilling, Blake E Dewey, David A Bennett, Sid O'Bryant, Robert C Barber, Derek Archer, Timothy J Hohman, Shunxing Bao, Zhiyuan Li, Bennett A Landman, Nazirah Mohd Khairi, Alzheimer’s Disease Neuroimaging Initiative, HABS-HD Study Team

“…Most efforts to reduce data QC time rely on quantitative outlier detection, which cannot capture every instance of algorithm failure. …”
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Small Scale Multi-Object Segmentation in Mid-Infrared Image Using the Image Timing Features–Gaussian Mixture Model and Convolutional-UNet by Meng Lv, Haoting Liu, Mengmeng Wang, Dongyang Wang, Haiguang Li, Xiaofei Lu, Zhenhui Guo, Qing Li

“…Furthermore, the proposed algorithm meets real-time processing requirements, confirming its capability to enhance small-target detection in complex outdoor environments and supporting the automation of grassland monitoring and enforcement.…”
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A Review on Fall Prediction and Prevention System for Personal Devices: Evaluation and Experimental Results by Masoud Hemmatpour, Renato Ferrero, Bartolomeo Montrucchio, Maurizio Rebaudengo

“…Kinematic features obtained from the data collected from accelerometer and gyroscope have been evaluated in combination with different machine learning algorithms. …”
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Real-Time Deep Intelligence Analysis and Visualization of COVID-19 Using FCNN Mechanism by Cherukuri Triveni, K. Suvarna Vani, M. Likhitha

“…Database management with respect to virus deep analysis is a critical task to the researcher through conventional algorithms. The RNA, DNA, and biological data are helping to the bio-inspired algorithm but its implementation can be complex by software tools. …”
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Artificial Intelligence in Glioblastoma—Transforming Diagnosis and Treatment by Alen Rončević, Nenad Koruga, Anamarija Soldo Koruga, Robert Rončević

“…Furthermore, machine learning models can integrate multimodal data to develop personalized treatments. …”
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Development of a Japanese polygenic risk score model for amyloid-β PET imaging in Alzheimer’s disease by Misato Kaishima, Junichi Ito, Kentaro Takahashi, Kenji Tai, Junro Kuromitsu, Shogyoku Bun, Daisuke Ito

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Artificial intelligence for screening and early diagnosis of pancreatic neoplasms in the context of centralization of the laboratory service in the region by S. I. Panin, V. A. Suvorov, A. V. Zubkov, S. A. Bezborodov, A. A. Panina, N. V. Kovalenko, A. R. Donsckaia, I. G. Shushkova, A. V. Bykov, Ya. A. Marenkov

“…The creation of software based on the selected algorithm will make it possible to clarify the real effectiveness of machine learning on a larger population of patients with pancreatic neoplasms.…”
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Terminal-based method for efficient inter-turn fault localization and severity assessment in transformer windings by K. Lakshmi Prasanna, Manoj Samal, Mithun Mondal

“…However the existing methods based on calculation of fault factors, machine learning methods, and statistical indices require additional terminals or internal tap points, extensive training data and high computational demands, and limited applicability due to non-standardization and specific frequency band selection. …”
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Advancing Spike Sorting Through Gradient‐Based Preprocessing and Nonlinear Reduction With Agglomerative Clustering by Mohammad Amin Lotfi, Fatemeh Zareayan Jahromy, Mohammad Reza Daliri

“…Furthermore, in the synthetic data, the efficacy of our proposed models was evident in both unit detection and spike clustering. …”
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Optimized wavelength selection for eggplant seed vitality classification using information acquisition techniques by Bing Yang, Xuyang Liu, Dongfang Zhang, Dongfang Zhang, Xiaofei Fan, Xiaofei Fan, Bo Peng, Jun Zhang, Jun Zhang

“…In response to the need for efficient and nondestructive assessment methods, this study explores the use of hyperspectral imaging combined with advanced feature selection and classification algorithms to evaluate eggplant seed viability. Hyperspectral imaging was employed to collect spectral data from eggplant seeds, covering 360 bands within a wavelength range of 395.24–1008.20 nm. …”
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A Novel THz Differential Spectral Clustering Recognition Method Based on t-SNE by Tie-Jun Li, Chih-Cheng Chen, Jian-jun Liu, Gui-fang Shao, Christopher Chun Ki Chan

“…Second, we improve computation efficiency by mapping spectrum data samples from high-dimensional space to low-dimensional space by the use of a manifold learning algorithm (t-SNE). …”
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Enhanced Mobile Multiple-Input Multiple-Output Underwater Acoustic Communications by Kexin Zhao, Jun Ling, Jian Li

“…Under the assumption that the channels between all the transmitter and receiver pairs experience the same Doppler frequency, a variation of the recently proposed generalization of the sparse learning via iterative minimization (GoSLIM) algorithm, referred to as GoSLIM-V, is employed to estimate the frequency modulated acoustic channels. …”
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Optimized decomposition and identification method for multiple power quality disturbances by Wang Zhaoqing, Chang Yanzhao, Chen Jianlei, Bao Weiyu

“…The synergy of IVMD and OSVM enables the detection of multiple PQDs, remarkably even with a minimal amount of training data. …”
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Prediction of Chemical Corrosion Rate and Remaining Life of Buried Oil and Gas Pipelines in Changqing Gas Field by Xianbing Li, Rui Liu, Dong Ma, Yang Bai, Yukai Shi, Badm Anhouck

“…By improving the inertial weights and learning factors of the traditional particle swarm algorithm, the parameters of the generalized regression neural network are optimized and selected, and the corrosion rate prediction model of buried pipelines is finally constructed. …”
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Incorporating Wave-ViT for Breast Cancer Diagnosis Using MRI Imaging by Sahil Mahey, Hamid Usefi

“…Our approach consistently demonstrated over 94\% accuracy on the external validation dataset, showcasing the potential of machine learning algorithms like Wave-ViT to reduce diagnostic workloads and improve breast cancer detection outcomes. …”
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Automatic adventitious respiratory sound analysis: A systematic review. by Renard Xaviero Adhi Pramono, Stuart Bowyer, Esther Rodriguez-Villegas

“…<h4>Objective</h4>To provide a review of existing algorithms for the detection or classification of adventitious respiratory sounds. …”
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Robust outdoor trajectory mapping using CNN features and loop closure optimization by Kamran Kazi, Arbab Nighat Kalhoro, Farida Memon, Tarique Rafique Memon, Azam Rafique Memon

“…This paper introduces a robust framework for outdoor trajectory mapping that synergizes deep learning-based feature extraction with loop closure detection and optimization to address these limitations. …”
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