Intelligent Detection of Underwater Defects in Concrete Dams Based on YOLOv8s-UEC by Chenxi Liang, Yang Zhao, Fei Kang

“…This study proposes a concrete dam underwater apparent defect detection algorithm named YOLOv8s-UEC for intelligent identification of underwater defects. …”
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Histogram of Maximal Optical Flow Projection for Abnormal Events Detection in Crowded Scenes by Ang Li, Zhenjiang Miao, Yigang Cen, Tian Wang, Viacheslav Voronin

“…In this paper, based on a novel motion feature descriptor, that is, the histogram of maximal optical flow projection (HMOFP), we propose an algorithm to detect abnormal events in crowded scenes. …”
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Flexi-YOLO: A lightweight method for road crack detection in complex environments. by Jiexiang Yang, Renjie Tian, Zexing Zhou, Xingyue Tan, Pingyang He

“…Road crack detection is critical to global infrastructure maintenance and public safety, and complex background environments and nonlinear damage crack patterns challenge the need for real-time, efficient, and accurate detection.This paper proposes a lightweight yet robust Flexi-YOLO model based on the YOLOv8 algorithm. …”
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A Fault Detection Framework for Rotating Machinery with a Spectrogram and Convolutional Autoencoder by Hoyeon Lee, Jaehong Yu

“…Finally, we construct the fault detection model by applying the one-class classification algorithm to the latent feature vectors of training signals. …”
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UAV-based inspection of wind turbine blade surface defects detection technology by TAN Xingguo, ZHANG Gaoming

“…The experimental results show that the detection accuracy of the proposed method for typical blade defects such as trachoma, scratch and crack is above 90%, especially the detection accuracy of crack defects can reach 95%, which verifies the effectiveness and accuracy of the algorithm in blade detection.…”
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Machine learning for Internet of things anomaly detection under low-quality data by Shangbin Han, Qianhong Wu, Yang Yang

“…To address this problem, we give a detailed review and evaluation of six supervised anomaly detection methods, as well as release the core code of feature extractor for pcap format traffic traces and anomaly detection methods for reuse. …”
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YOLO-HVS: Infrared Small Target Detection Inspired by the Human Visual System by Xiaoge Wang, Yunlong Sheng, Qun Hao, Haiyuan Hou, Suzhen Nie

“…To address challenges of background interference and limited multi-scale feature extraction in infrared small target detection, this paper proposes a YOLO-HVS detection algorithm inspired by the human visual system. …”
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Detecting anomalies in blockchain transactions using machine learning classifiers and explainability analysis by Mohammad Hasan, Mohammad Shahriar Rahman, Helge Janicke, Iqbal H. Sarker

“…This study seeks to overcome this limitation by integrating explainable artificial intelligence (XAI) techniques and anomaly rules into tree-based ensemble classifiers for detecting anomalous Bitcoin transactions. The shapley additive explanation (SHAP) method is employed to measure the contribution of each feature, and it is compatible with ensemble models. …”
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Detection of external defects on potatoes by hyperspectral imaging technology and image processing method by Su Wenhao, Liu Guishan, He Jianguo, Wang Songlei, He Xiaoguang, Wang Wei, Wu Longguo

“…The traditional classification method has low efficiency and poor objectivity, costs big labor intensity, and is difficult to identify shortcomings through it.In order to realize the accurate and fast classification of potatoes in the process of actual processing, various potatoes with external defects were detected in spectral region of 400 - 1 000 nm using hyperspectral image technology, and an online nondestructive testing method was established by principal component analysis of characteristic wavelengths and image subtraction algorithm.Six defective potato types (mechanical damage, hole, scab, surface bruise, sprout, green skin, normal) and one qualified potato type were used as the research objects in this study, and their hyperspectral images were obtained, respectively. …”
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Pear Fruit Detection Model in Natural Environment Based on Lightweight Transformer Architecture by Zheng Huang, Xiuhua Zhang, Hongsen Wang, Huajie Wei, Yi Zhang, Guihong Zhou

“…The CCFM module is reconstructed based on the Slim-Neck method, and the loss function of the original model is replaced with the Shape-NWD small target detection mechanism loss function to enhance the feature extraction capability of the network. …”
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YOLO-Ginseng: a detection method for ginseng fruit in natural agricultural environment by Zhedong Xie, Zhuang Yang, Chao Li, Zhen Zhang, Jiazhuo Jiang, Hongyu Guo

“…Therefore, this study proposes the YOLO-Ginseng detection method.MethodsFirstly, this detection method innovatively proposes a plug-and-play deep hierarchical perception feature extraction module called C3f-RN, which incorporates a sliding window mechanism. …”
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Proposing Smart System for Detecting and Monitoring Vehicle Using Multiobject Multicamera Tracking by Phat Nguyen Huu, Bang Nguyen Anh, Quang Tran Minh

“…Our system leverages data collected from traffic surveillance cameras and harnesses the power of deep learning technology to detect and track vehicles smoothly. To achieve this, we use the YOLO model for detection in conjunction with the DeepSORT algorithm for precise vehicle tracking on each camera. …”
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Research on Road Crack Detection Based on RGB-LPC-GPR Data Fusion by Z. Wang, D. Qiu, R. Wu, R. Wu, Y. Shi, W. Niu

“…A Cross-Attention Transformer combined with a Feature Pyramid Network (FPN) was used for dynamic feature weighting, achieving a crack detection IoU of 97.3% and an AP@0.5 of 93.7% for underground void detection, thereby substantially enhancing the model's performance in detecting complex road damage. …”
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Deep Reinforcement Learning-Based Motion Control Optimization for Defect Detection System by Yuhuan Cai, Liye Zhao, Xingyu Chen, Zhenjun Li

“…Specifically, the TD3 algorithm, featuring a dual-critic structure, is employed to enhance control precision within predefined state and action spaces. …”
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Using Deep Learning Techniques to Enhance Blood Cell Detection in Patients with Leukemia by Mahwish Ilyas, Muhammad Bilal, Nadia Malik, Hikmat Ullah Khan, Muhammad Ramzan, Anam Naz

“…To accomplish this task, we use digital image processing techniques and then apply the convolutional neural network (CNN) deep learning algorithm to blood sample images. This research employs a multi-stage methodology, including data preparation, data preprocessing, feature extraction, and then classification. …”
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Tea Disease Detection Method Based on Improved YOLOv8 in Complex Background by Junchen Ai, Yadong Li, Shengxiang Gao, Rongsheng Hu, Wengang Che

“…Experimental results show that the proposed YOLO-SSM algorithm has obvious advantages in accuracy and model complexity and can provide reliable theoretical support for efficient and accurate detection and identification of tea leaf diseases in natural scenes.…”
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PCPE-YOLO with a lightweight dynamically reconfigurable backbone for small object detection by Weijia Chen, Jiaming Liu, Tong Liu, Yaoming Zhuang

“…In this paper, we propose PCPE-YOLO, a novel object detection algorithm, specifically designed to address these difficulties. …”
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Research on Underwater Target Detection Technology Based on SMV-YOLOv11n by Dongcheng Liao, Yijun Shen, Jinyu Ou, Yanlian Du

“…To address these issues, this paper proposes an underwater object detection algorithm named SMV-YOLOv11. Firstly, the Swin Transformer is adopted to replace the backbone network, and a novel Multi-scale Spatial and Channel Attention module (MSCA) is designed and integrated into the backbone to enhance its feature extraction capability. …”
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Non-Destructive Detection of Soybean Storage Quality Using Hyperspectral Imaging Technology by Yurong Zhang, Wenliang Wu, Xianqing Zhou, Jun-Hu Cheng

“…The study focused on acquiring raw spectral information using hyperspectral imaging technology, preprocessing by the derivative method (1ST, 2ND), multiplicative scatter correction (MSC), and standard normal variate (SNV). The feature variables were extracted by a variable iterative space shrinkage approach (VISSA), competitive adaptive reweighted sampling (CARS), and a successive projections algorithm (SPA). …”
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Railway Foreign Object Intrusion Detection Using UAV Images and YOLO-UAT by Yang Yang, Zhanhao Liu, Junming Chen, Haiming Gao, Tao Wang

“…Then the EfficientNet network is employed to replace the backbone extraction network of YOLOv5s, achieving a lightweight model that enhances detection speed. Secondly, a C<inline-formula> <tex-math notation="LaTeX">$3\_$ </tex-math></inline-formula> CBAM module is constructed to enhance feature extraction and enhance the model&#x2019;s detection ability for small-scale targets. …”
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