Evaluation of the Finis Swimsense® and the Garmin Swim™ activity monitors for swimming performance and stroke kinematics analysis. by Robert Mooney, Leo R Quinlan, Gavin Corley, Alan Godfrey, Conor Osborough, Gearóid ÓLaighin

“…Further development to improve accuracy of feature detection algorithms, specifically for lap time and stroke count, would also increase their suitability within competitive settings.…”
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A Unified Approach to Image Recognition and Cryptography via Flexible Weak Inverse Property Quasigroups by Mohammad Mazyad Hazzazi, Muhammad Nadeem, Muhammad Kamran, Muhammad Arshad, Samuel Asefa Fufa

“…It also addresses the implementation of polynomial functions PTt in image and pattern detection, with emphasis on feature extraction and edge detection. …”
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Diagnosis of Device Exception Based on Causality of Device Indicators by Zhaohui Wang, Yan Wei, Longhua Shang, Shiwei Zhang, Shixiong Bao, Zhengren Li

“…The framework operates in three stages: 1) Causality Detection (CD) employs the LASAR algorithm to construct sparse causal graphs from monitoring variables. 2) Prediction of Device Status (PODS) leverages GraphSAGE to extract spatio-temporal features from causal graphs for state prediction. 3) Diagnosis of Exception (DOE) utilizes kernel density estimation (KDE) for distribution-agnostic anomaly scoring. …”
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A Two-Stage Method for Diagnosing COVID-19, Leveraging CNN, and Transfer Learning on CT Scan Images by Touba torabipour, Abolfazl Gandomi, Mohammad Ghanimi

“…Utilizing deep learning algorithms and machine vision, computer scientists have devised a method for automated detection of this disease. …”
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Towards Automatic Expressive Pipa Music Transcription Using Morphological Analysis of Photoelectric Signals by Yuancheng Wang, Xuanzhe Li, Yunxiao Zhang, Qiao Wang

“…The captured signal demonstrates a distinctive arched feature during plucking. This facilitates onset detection to avoid the impact of the spurious energy peaks within vibration areas that arise from pitch-shift playing techniques. …”
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Research on Method for Intelligent Recognition of Deep-Sea Biological Images Based on PSVG-YOLOv8n by Dali Chen, Xianpeng Shi, Jichao Yang, Xiang Gao, Yugang Ren

“…Nonetheless, the inherent complexities of the deep-sea environment, the scarcity of available deep-sea organism samples, and the significant refraction and scattering effects of underwater light collectively impose formidable challenges on the current detection algorithms. To address these issues, we propose an advanced deep-sea biometric identification framework based on an enhanced YOLOv8n architecture, termed PSVG-YOLOv8n. …”
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Protecting Industrial Control Systems From Shodan Exploitation Through Advanced Traffic Analysis by Sayed Reza Ghazinour Naeini, Alireza Shameli-Sendi, Masoume Jabbarifar

“…This research introduces protocol analysis as a novel feature in network traffic analysis, significantly improving detection accuracy over models that rely solely on traditional network features. …”
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High-Quality Multispectral Image Reconstruction for the Spectral Camera Based on Ghost Imaging via Sparsity Constraints Using CoT-Unet by Tao Hu, Jianxia Chen, Shu Wang, Jianrong Wu, Ziyan Chen, Zhifu Tian, Ruipeng Ma, Di Wu

“…To solve the problem of poor quality in ghost imaging via sparsity constraints (GISC) multispectral image reconstruction with correlation operations and compressed sensing algorithms under low sampling rate detection conditions, we propose an end-to-end deep-learning-based method. …”
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A Hybrid Learning Framework for Enhancing Bridge Damage Prediction by Amal Abdulbaqi Maryoosh, Saeid Pashazadeh, Pedram Salehpour

“…The proposed approach combines pixel-based feature method local binary pattern (LBP) with the mid-level feature bag of visual words (BoVW) for feature extraction, followed by the Apriori algorithm for dimensionality reduction and optimal feature selection. …”
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TrainNet for locking state recognition of side door of railway freight car by Ning Xing, Cai Kangcheng, Zhou Shumin, Lan Xiangui, Lai Yihui

“…An LSKCSPC module is also introduced to capture a dynamic receptive field, enabling TrainNet to adjust its receptive field dynamically to the scale of the object, improving its feature representation capacity. Furthermore, the detection head for small-scale objects is redesigned, the feature layer size is increased to enhance the ability to extract and detect fine-grained features. …”
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An efficient cost calculation method for disparity estimation of stereo matching considering shadow occlusion by Hongjun Sha, Wei Yuan, Xunping Wang, Xiuliu Yuan, Shunichi Koshimura

“…This research work proposes a novel cost calculation method that considers shadow occlusion areas to address the issues of poor disparity estimation in urban areas, termed Matching Cost based on Shadow Properties (MCSP), error estimation of the shadow occlusion area, which not only considers the problem of disparity error estimation in the shadow occlusion areas but also considers the problem of edge integrity and smoothness in the disparity estimation results. Firstly, a shadow detection model is established through the double constraints of spatial angle and distance to detect and mark the shadow areas in complex scenarios self-adaptively. …”
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Method of troubleshooting in the neural network environment of intellectual decision supporting systems by О.І. Тимочко, С.В. Осієвський, О.О. Тімочко, П.В. Бєляєв

“…It is shown that to detect these types of errors it is advisable to use a modified GLARE algorithm with the adaptation procedure. …”
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A YOLOv8n-T and ByteTrack-Based Dual-Area Tracking and Counting Method for Cucumber Flowers by Liyang Su, Shujuan Zhang, Hongtu Zhang, Xiangsen Meng, Xiongkui He

“…Accurate counting of cucumber flowers using intelligent algorithms to monitor their sex ratio is essential for intelligent facility agriculture management. …”
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HSDT-TabNet: A Dual-Path Deep Learning Model for Severity Grading of Soybean Frogeye Leaf Spot by Xiaoming Li, Yang Zhou, Yongguang Li, Shiqi Wang, Wenxue Bian, Hongmin Sun

“…However, both conventional field monitoring and machine learning algorithms remain challenged in achieving rapid and accurate detection. …”
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On the Prediction and Forecasting of PMs and Air Pollution: An Application of Deep Hybrid AI-Based Models by Youness El Mghouchi, Mihaela Tinca Udristioiu

“…The methodology consists of three main phases: (i) data preprocessing, including anomaly detection and missing value handling; (ii) exploratory analysis to identify trends and correlations between PM concentrations (PMs) and predictor variables; and (iii) model development using 23 machine learning and deep learning algorithms, enhanced by 50 feature selection techniques. …”
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A synergistic PCA and C-A fractal approach for high-precision extraction of mineral alteration anomalies from ASTER remote sensing data by Yidan Zhu, Zhichun Wu

“…Subsequently, the C-A fractal method quantifies alteration intensity, utilizing a grid-based segmentation and change-point model to classify alteration levels and distinguish them from other geological features. This approach refines anomaly detection, overcoming the limitations of traditional techniques and improving classification accuracy. …”
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Data Mining Classification Techniques for Diabetes Prediction by Hindreen Rashid Abdulqadir, Adnan Mohsin Abdulazeez, Dilovan Assad Zebari

“…The detection and prediction of diseases is an aspect of classification and prediction. …”
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Klasifikasi Penyakit Daun Pada Tanaman Jagung Menggunakan Algoritma Support Vector Machine, K-Nearest Neighbors dan Multilayer Perceptron by Jaka Kusuma, Rubianto, Rika Rosnelly, Hartono, B. Herawan Hayadi

“…This study will compare classification algorithms, namely Support Vector Machine, K-Nearest Neighbors, and Multilayer Perceptron to find the best algorithm in the classification of leaf disease in corn plants, namely, cercospora leaf spot gray, common rust, and northern leaf blight using the VGG-16 deep learning model used as image feature extraction. …”
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An Efficient Deep Learning-Based Framework for Predicting Cyber Violence in Social Networks by Younes Fayand Fathabad, Mohammad Ali Balafar, Amin Golzari Oskouei, Kamal Koohi

“…However, this has also increased the prevalence of cyber violence, necessitating the development of automated detection methods. Deep learning-based algorithms have proven effective in identifying violent content, yet existing models often struggle with understanding contextual nuances and implicit forms of cyber violence. …”
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ULOTrack: Underwater Long-Term Object Tracker for Marine Organism Capture by Ju He, Yang Yu, Hongyu Wei, Hu Xu

“…ULOTrack is based on a performance discrimination and re-detection framework and constitutes three modules: (1) an object tracker, which can extract multi-feature information of the underwater target; (2) a multi-layer tracking performance discriminator, which serves the purpose of evaluating the stability of the current tracking state, thereby reducing potential model drift; and (3) lightweight detection, which can predict the candidate boxes to relocate the lost tracked underwater object. …”
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