Transmission Line Anomaly Detection and Real-Time Monitoring System Combining Edge Computing and EfficientDet by Menghao Lin, Yang Ding, Tianle Wang, Yang Liu, Zewei Li

“…Firstly, by collecting abnormal images of transmission channels, the Retinex algorithm is used to enhance the input images. Secondly, in order to improve the speed of model detection, the convolution operation process for obtaining data features based on Ghost lightweight module is reconstructed. …”
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EHA-YOLOv5: An Efficient and Highly Accurate Improved YOLOv5 Model for Workshop Bearing Rail Defect Detection Application by Jiyong Hu, Hongfei Yang, Jiatang He, Dongxu Bai, Hongda Chen

“…Initially, a Multi-Scale Pyramid Pooling (MSPP) module, incorporating the concept of residual stacking, is introduced to effectively enhance the extraction of complex features; Subsequently, the coordinate attention mechanism is optimized, leading to the development of a novel Spatial Coordinate Attention Mechanism (DAM), focused on detecting small-sized defects; Thereafter, a Dual Sampling Transition Module (DSTM) is applied to enhance information retention during the down-sampling process; Finally, the DBDAMN clustering algorithm is utilized to optimize anchor sizes, allowing for more precise adaptation to the diversity of defect sizes. …”
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A Tunnel Crack Detection Method Based on an Unmanned Aerial Vehicle (UAV) Equipped with a High-Speed Camera and Crack Recognition Algorithm Using Improved Multi-Scale Retinex and P... by Wei Sun, Xiaohu Liu, Zhiyong Lei

“…In order to solve the problems of low efficiency and accuracy in the traditional detection of tunnel cracks, this paper proposes a tunnel crack detection method based on a UAV (unmanned aerial vehicle) equipped with a high-speed camera and a crack recognition algorithm using the improved multi-scale Retinex (MSR) algorithm and the Prewitt–Otsu algorithm, aiming to improve the accuracy and efficiency of detection. …”
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A feature selection method utilizing path accumulation cost, redundancy minimization, and interaction maximization for the diagnosis of coronary heart disease by Jiayao Jiang, Zheng Yue, Hongling Zhu, Yan Wang, Hongsen Cai, Wenguang Hou

“…Results Experimental outcomes demonstrate that our algorithm outperforms several classical algorithms in terms of classification accuracy and feature dimension reduction, while also identifying highly correlated feature subsets. …”
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Detection of Battery Appearance Defects Based on Multi‑Scale Object Detection by LI Yang, ZHANG Jianliang, ZHAO Min, WU Jian, HAN Chao, DANG Xiaoyan, WANG Huifang

“…[Purposes] Based on YOLO v4 framework, a new feature extraction network VoVNet-A algorithm was designed, which can effectively identify image fine-grained features. …”
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Classification of Fritillaria thunbergii appearance quality based on machine vision and machine learning technology by DONG Chengye, LI Dongfang, FENG Huaiqu, LONG Sifang, XI Te, ZHOU Qin’an, WANG Jun

“…Several statistical learning and object detection algorithms were selected to train and test the F. thunbergii dataset. …”
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Features Image Matchingof SUＲF and ＲANSAC by WANG Wei-bing, BAI Xiao-ling, XU Qian

“…As a result，an adaptable algorithm is proposed to optimize image matching. Firstly，the SUＲF operator is used for feature detection and feature description. …”
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LGN-YOLO: A Leaf-Oriented Region-of-Interest Generation Method for Cotton Top Buds in Fields by Yufei Xie, Liping Chen

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A human visual cognitive mechanism based network for surface defect detection(基于人类视觉认知机制的表面缺陷检测) by 崔丽莎(CUI Lisha), 代润鹏(DAI Runpeng), 姜晓恒(JIANG Xiaoheng), 李飞蝶(LI Feidie), 陈恩庆(CHEN Enqing), 徐明亮(XU Mingliang)

“…HVCM-Net achieves superior detection performance on defect datasets GB-DET, NEU-DET, and DAGM2007 compared to other algorithms, demonstrating the effectiveness of the proposed method.…”
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Link Prediction in Social Networks Using the HTOA by Foad Asef, Vahid Majidnezhad, Mohammad-Reza Feizi-Derakhshi

“…This study introduces a novel approach to link prediction in social networks by employing the Heat Transfer Optimization Algorithm (HTOA) for topological feature selection. …”
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Research on soybean leaf disease recognition in natural environment based on improved Yolov8 by Chen Chen, Chen Chen, Xiaolei Lu, Lei He, Lei He, Ruoxue Xu, Ruoxue Xu, Yi Yang, Yi Yang, Jing Qiu, Jing Qiu

“…A lightweight detection head (LSCD) is further introduced to facilitate multiscale feature interactions while reducing the overall model parameter count. …”
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A Novel Supervoxel-Based NE-PC Model for Separating Wood and Leaf Components from Terrestrial Laser Scanning Data by Shengqin Gong, Xin Shen, Lin Cao

“…First, the boundary-preserved supervoxel segmentation (BPSS) algorithm was adapted to generate supervoxels for calculating geometric features and representative points for constructing the undirected graph. …”
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An intelligent object detection and classification framework for assisting visually challenged persons using deep learning and improved crow search optimization by Alaa O. Khadidos, Ayman Yafoz

“…This study proposes a Hybrid DL Model for Object Detection and Classification Using an Improved Crow Search Algorithm (HDLMODC-ICSA) method. …”
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DentoMorph-LDMs: diffusion models based on novel adaptive 8-connected gum tissue and deciduous teeth loss for dental image augmentation by Hanaa Salem Marie, Mostafa Elbaz, Riham sobhy Soliman, Amira Abdelhafeez elkhatib

“…We developed two novel biologically-inspired loss functions integrated within LDMs specifically designed for pediatric dental imaging: Gum-Adaptive Pixel Imputation (GAPI) utilizing adaptive 8-connected pixel neighborhoods that mimic pediatric gum tissue adaptive behavior, and Deciduous Transition-Based Reconstruction (DTBR) incorporating developmental stage awareness based on primary teeth transition patterns observed in children aged 2–12 years. These algorithms guide the diffusion process toward developmentally appropriate reconstructions through specialized loss functions that preserve structural continuity of deciduous dentition and age-specific anatomical features crucial for accurate pediatric diagnosis. …”
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Algorithm for the analysis of kinematic characteristics of running by N. S. Davydova, V. Е. Vasiuk, N. A. Paramonova, М. М. Mezhennaya, D. I. Guseinov

“…The paper describes an algorithm for analysis of kinematic characteristics of the running based on inertial gyro signals. …”
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Mechanism–Data Collaboration for Characterizing Sea Clutter Properties and Training Sample Selection by Wenhao Chen, Yong Zou, Zhengzhou Li, Shengrong Zhong, Haolin Gan, Aoran Li

“…Multi-feature-based maritime radar target detection algorithms often rely on statistical models to accurately characterize sea clutter variations. …”
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Early Parkinson’s disease identification via hybrid feature selection from multi-feature subsets and optimized CatBoost with SMOTE by Subhashree Mohapatra, Bhanja Kishor Swain, Manohar Mishra

“…Given the critical role of precise PD classification in medical diagnostics, this study proposes a novel framework to enhance detection accuracy. The proposed framework leverages a strong categorical boosting (CatBoost) algorithm optimized using Grid Search Optimization (GSO). …”
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Potential Use of a New Energy Vision (NEV) Camera for Diagnostic Support of Carpal Tunnel Syndrome: Development of a Decision-Making Algorithm to Differentiate Carpal Tunnel-Affect... by Dror Robinson, Mohammad Khatib, Mohammad Eissa, Mustafa Yassin

“…This study evaluates the New Energy Vision (NEV) camera, an RGB-based multispectral imaging tool, to detect CTS through skin texture and color analysis, developing a machine learning algorithm to distinguish CTS-affected hands from controls. …”
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Detecting Anomalies in Hydraulically Adjusted Servomotors Based on a Multi-Scale One-Dimensional Residual Neural Network and GA-SVDD by Xukang Yang, Anqi Jiang, Wanlu Jiang, Yonghui Zhao, Enyu Tang, Zhiqian Qi

“…Finally, an abnormal detection model for the hydraulically adjusted servomotor was constructed by optimizing the support vector data domain based on this feature set using a genetic algorithm. …”
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An Optimized Transformer–GAN–AE for Intrusion Detection in Edge and IIoT Systems: Experimental Insights from WUSTL-IIoT-2021, EdgeIIoTset, and TON_IoT Datasets by Ahmad Salehiyan, Pardis Sadatian Moghaddam, Masoud Kaveh

“…In this study, we propose an optimized hybrid DL framework that combines a transformer, generative adversarial network (GAN), and autoencoder (AE) components, referred to as Transformer–GAN–AE, for robust intrusion detection in Edge and IIoT environments. To enhance the training and convergence of the GAN component, we integrate an improved chimp optimization algorithm (IChOA) for hyperparameter tuning and feature refinement. …”
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