Robot Visual Tracking Model Based on Improved GOTURN-LD Algorithm by Lijuan Xu, Dalong Liu, Huanjian Ma

“…Therefore, this paper studies the use of the You Only Look Once series algorithm and the use of the regression network general target tracking algorithm to improve the detection and tracker part of the track-learning-detection algorithm. …”
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A Space-Time Plume Algorithm to Represent and Compute Dynamic Places by Brent Dell, May Yuan

“…Building on this, we developed Space-Time Plume, a new algorithm for detecting and tracking evolving event clusters as smoke plumes in space and time, representing dynamic places. …”
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YOLO-HF: Early Detection of Home Fires Using YOLO by Bo Peng, Tae-Kook Kim

“…This gap causes object detection algorithms to produce high false positive and false negative rates in research on the early detection of such fires. …”
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Application of computer vision algorithm in ceramic surface texture analysis and prediction by Yao Tian, Feifei Zhu

“…In order to improve the surface quality of ceramic products, this paper proposes a ceramic surface texture recognition analysis and texture generation prediction method based on computer vision algorithm. In this method, laser lines are used to scan along the radial direction of ceramic, and the position of laser stripe is located by straight line detection algorithm. …”
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Identification of hypertension gene expression biomarkers based on the DeepGCFS algorithm. by Zongjin Li, Liqin Tian, Libing Bai, Zeyu Jia, Xiaoming Wu, Changxin Song

“…The algorithm then uses hybrid clustering methods for gene module detection. …”
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Precision Marketing Method of E-Commerce Platform Based on Clustering Algorithm by Bei Zhang, Luquan Wang, Yuanyuan Li

“…In addition, based on the idea of the K-mode clustering algorithm, this paper proposes a clustering method combining related rules with multivalued discrete features (MDF). …”
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Image Inpainting Algorithm Based on Structure-Guided Generative Adversarial Network by Li Zhao, Tongyang Zhu, Chuang Wang, Feng Tian, Hongge Yao

“…The proposed methodology advances a two-stage restoration paradigm: (1) Structural Prior Extraction, where adaptive edge detection algorithms identify residual contours in corrupted regions, and a transformer-enhanced network reconstructs globally consistent structural maps through contextual feature propagation; (2) Structure-Constrained Texture Synthesis, wherein a multi-scale generator with hybrid dilated convolutions and channel attention mechanisms iteratively refines high-fidelity textures under explicit structural guidance. …”
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Segmentation of Stone Slab Cracks Based on an Improved YOLOv8 Algorithm by Qitao Tian, Runshu Peng, Fuzeng Wang

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TRANS: a prediction model for EGFR mutation status in NSCLC based on radiomics and clinical features by Zhigang Chen, Huiying Lu, Ao Liu, Jia Weng, Lei Gan, Lina Zhou, Xiao Ding, Shicheng Li

“…Methods The study enrolled 254 NSCLC patients of four cohorts: the Affiliated Hospital of Qingdao University (AHQU, n = 54), the Second Affiliated Hospital of Soochow University (SAHSU, n = 78), TCGA-NSCLC (n = 91), and CPTAC-NSCLC (n = 31). Radiomic features were extracted using the LIFEx software. The least absolute shrinkage and selection operator (LASSO) algorithm was utilized to select predictive features of CT radiomics, clinical data, and RNA sequencing, which were evaluated using receiver operating characteristic (ROC) curves. …”
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Analysis and Prediction of CET4 Scores Based on Data Mining Algorithm by Hongyan Wang

“…The weight K of the input feature and the adjacent feature are weighted, although the allocation algorithm of the adjacent classification effect has not been significantly improved, but the stability classification is better than K-nearest neighbor algorithm, its classification efficiency is greatly improved, classification time is greatly reduced, and classification efficiency is increased by 119%. …”
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Photovoltaic module dataset for automated fault detection and analysis in large photovoltaic systems using photovoltaic module fault detectionMendeley Data by Rotimi-Williams Bello, Pius A. Owolawi, Etienne A. van Wyk, Chunling Du

“…Because the data comes from a single-day collection and one week laboratory experiment, it makes the data more suitable for testing algorithms designed for fault detection. The dataset is publicly and freely available to the scientific community at 10.17632/5ssmfpgrpc.1…”
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Heart Disease Prediction Using Ensemble Tree Algorithms: A Supervised Learning Perspective by Enoch Sakyi-Yeboah, Edmund Fosu Agyemang, Vincent Agbenyeavu, Akua Osei-Nkwantabisa, Priscilla Kissi-Appiah, Lateef Moshood, Lawrence Agbota, Ezekiel N. N. Nortey

“…These metrics indicate a superior ability to distinguish between patients with and without heart disease, effectively making it particularly valuable for clinical applications where early detection can save lives. The SHapley Additive exPlanations (SHAP) framework adopted to investigate the relative importance of the features in predicting heart disease revealed the most influential predictors (ST slope, chest pain type, old peak, and cholesterol), further aiding the understanding of heart disease mechanisms. …”
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Enhancing Intrusion Detection Systems with Dimensionality Reduction and Multi-Stacking Ensemble Techniques by Ali Mohammed Alsaffar, Mostafa Nouri-Baygi, Hamed Zolbanin

“…We employ the LogitBoost algorithm with XGBRegressor for feature selection, complemented by a Residual Network (ResNet) deep learning model for feature extraction. …”
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Independently Identifying Noise Clusters in 2D LiDAR Scanning with Clustering Algorithms by Chiew Wei Wen, Chuan Hsian Pu

“…LiDAR environmental mapping technology is often highly praised for its precise mapping information with intricate features for various detection or tracking based applications. …”
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A Comparative Evaluation of Texture Features for Semantic Segmentation of Breast Histopathological Images by R. Rashmi, Keerthana Prasad, Chethana Babu K. Udupa, V. Shwetha

“…Support Vector Machine and Multi Layer Perceptron algorithms are trained to perform pixelwise classification. …”
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Dynamic analysis of malicious behavior propagation based on feature selection in software network by Huajian Xue, Huajian Xue, Yali Wang, Qiguang Tang

“…This paper introduces a dynamic analysis detection method for malicious behavior based on feature extraction (MBDFE), designed to effectively identify and thwart the spread of malicious software. …”
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Design and implementation algorithm of safe driver assistant system based on EOG by Zhao LYU, Xiao-pei WU, Chao ZHANG, Bing WEI

“…Furthermore, independent component analysis (ICA) algorithm was used to extract spatial feature parameters of activity-detected EOG signals, and combined with support vector machine (SVM) method to recognize the type of saccade signals, such as up-rolling, left-rolling and right-rolling. …”
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Adaptive GDDA-BLAST: fast and efficient algorithm for protein sequence embedding. by Yoojin Hong, Jaewoo Kang, Dongwon Lee, Damian B van Rossum

“…Herein, we describe the logic and algorithmic process for a heuristic embedding strategy named "Adaptive GDDA-BLAST." …”
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Thermal Runaway Warning of Lithium Battery Based on Electronic Nose and Machine Learning Algorithms by Zilong Pu, Miaomiao Yang, Mingzhi Jiao, Duan Zhao, Yu Huo, Zhi Wang

“…Characteristic gas detection can be an efficient way to predict the degree of thermal runaway of a lithium battery. …”
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Bridge Deformation Monitoring Combining 3D Laser Scanning with Multi-Scale Algorithms by Dongmei Tan, Wenjie Li, Yu Tao, Baifeng Ji

“…To address the inefficiencies and limited spatial resolution of traditional single-point monitoring techniques, this study proposes a multi-scale analysis method that integrates the Multi-Scale Model-to-Model Cloud Comparison (M3C2) algorithm with least-squares plane fitting. This approach employs the M3C2 algorithm for qualitative full-field deformation detection and utilizes least-squares plane fitting for quantitative feature extraction. …”
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