Efficient and Effective Detection of Repeated Pattern from Fronto-Parallel Images with Unknown Visual Contents by Hong Qu, Yanghong Zhou, P. Y. Mok, Gerhard Flatz, Li Li

“…The new method leverages deep features from a pre-trained Convolutional Neural Network (CNN) to estimate initial repeated pattern sizes and refines them using a dynamic autocorrelation algorithm. …”
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LRD-RB: The First Large-Scale Dataset With Rotated Bounding Boxes for Automated Lunar Rockfall Detection by Dingruibo Miao, Jianguo Yan, Zhigang Tu, Jean-Pierre Barriot

“…We conducted systematic evaluations of several representative rotated object detection models on LRD-RB. The dataset not only facilitates the development and testing of lunar rockfall detection algorithms but also has the potential to serve as a challenging benchmark for rotated small object detection tasks in remote sensing applications.…”
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Detection of Potentially Anomalous Cosmic Particle Tracks Acquired with CMOS Sensors: Validation of Rough k–Means Clustering with PCA Feature Extraction by Hachaj Tomasz, Piekarczyk Marcin, Wąs Jarosław

“…We apply a principal components analysis-based feature extraction method and rough k-means clustering for outlier detection. …”
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Three-dimensional ground-penetrating radar-based feature point tensor voting for semi-rigid base asphalt pavement crack detection by Zhiyong Huang, Guoyuan Xu, Xiaoning Zhang, Bo Zang, Huayang Yu

“…In this paper, the radar image is gridded by the ECA-ResNet network, and the center point of the detected crack grid is used as the feature point, and the continuous path of the crack is reconstructed by the tensor voting algorithm. …”
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A novel univariate feature selection with ANOVA F-test-based machine learning model for Intrusion Detection Framework of Robotics system by Narinder Verma, Neerendra Kumar, Kuljeet Singh, Abeer Aljohani, Anurag Sinha, Syed Abid Hussain

“…To evaluate the efficacy of the presented framework, an algorithm is also designed and tested using multiple machine-learning techniques. …”
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Enhancing IoT cybersecurity through lean-based hybrid feature selection and ensemble learning: A visual analytics approach to intrusion detection. by Islam Zada, Esraa Omran, Salman Jan, Hessa Alfraihi, Seetah Alsalamah, Abdullah Alshahrani, Shaukat Hayat, Nguyen Phi

“…The dynamical growth of cyber threats in IoT setting requires smart and scalable intrusion detection systems. In this paper, a Lean-based hybrid Intrusion Detection framework using Particle Swarm Optimization and Genetic Algorithm (PSO-GA) to select the features and Extreme Learning Machine and Bootstrap Aggregation (ELM-BA) to classify the features is introduced. …”
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A Hybrid Deep Learning and Improved SVM Framework for Real-Time Railroad Construction Personnel Detection with Multi-Scale Feature Optimization by Jianqiu Chen, Huan Xiong, Shixuan Zhou, Xiang Wang, Benxiao Lou, Longtang Ning, Qingwei Hu, Yang Tang, Guobin Gu

“…Finally, an SVM classification algorithm is employed for personnel detection. To process small sample categories, data enhancement techniques (e.g., random flip and rotation) and K-fold cross-validation are applied to optimize the model parameters. …”
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Hybrid Feature-Based Disease Detection in Plant Leaf Using Convolutional Neural Network, Bayesian Optimized SVM, and Random Forest Classifier by Ashutosh Kumar Singh, SVN Sreenivasu, U.S.B. K. Mahalaxmi, Himanshu Sharma, Dinesh D. Patil, Evans Asenso

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Machine Learning Aided Resilient Spectrum Surveillance for Cognitive Tactical Wireless Networks: Design and Proof-of-Concept by Eli Garlick, Nourhan Hesham, MD. Zoheb Hassan, Imtiaz Ahmed, Anas Chaaban, MD. Jahangir Hossain

“…The uniqueness of <inline-formula> <tex-math notation="LaTeX">$\textsf {MARSS}$ </tex-math></inline-formula> is its ability to detect hidden and unknown interference signals in multiple frequency bands without using any prior labels, thanks to its superior feature extraction capability. …”
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Multi-layer feature fusion and attention-enhanced YOLOv9 for rapid field detection of greenhouse blueberry maturity at long and short distances by Ziwei Pan, Lei Xu, Wanjin Zhao, Cong Fan, Xihao Zhang, Weihui Chen, Yonglin Shen, Nengcheng Chen

“…Therefore, this paper presents an improved algorithm, YOLOv9-MSAS, for detecting greenhouse blueberry maturity at long and short distances. …”
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A novel double machine learning approach for detecting early breast cancer using advanced feature selection and dimensionality reduction techniques by Suganya Athisayamani, Tamilazhagan S, A. Robert Singh, Jae-Yong Hwang, Gyanendra Prasad Joshi

“…These DML models, when combined with dimensionality reduction (PCA) and feature selection, significantly improve the performance of breast cancer detection systems by leveraging both structured and sequential data with high accuracy of 0.99.…”
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Using Features Extracted From Upper Limb Reaching Tasks to Detect Parkinson&#x2019;s Disease by Means of Machine Learning Models by Giuseppe Cesarelli, Leandro Donisi, Francesco Amato, Maria Romano, Mario Cesarelli, Giovanni D'Addio, Alfonso M. Ponsiglione, Carlo Ricciardi

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CubicPat: Investigations on the Mental Performance and Stress Detection Using EEG Signals by Ugur Ince, Yunus Talu, Aleyna Duz, Suat Tas, Dahiru Tanko, Irem Tasci, Sengul Dogan, Abdul Hafeez Baig, Emrah Aydemir, Turker Tuncer

“…Classification results were obtained using the cumulative weighted iterative neighborhood component analysis (CWINCA) feature selector and the t-algorithm-based k-nearest neighbors (tkNN) classifier. …”
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An Identification and Localization Method for 3D Workpiece Welds Based on the DBSCAN Point Cloud Clustering Algorithm by Nian Zhou, Ping Jiang, Shiliang Jiang, Leshi Shu, Xiaoxian Ni, Linjun Zhong

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The Fusion of Focused Spectral and Image Texture Features: A New Exploration of the Nondestructive Detection of Degeneration Degree in <i>Pleurotus geesteranus</i> by Yifan Jiang, Jin Shang, Yueyue Cai, Shiyang Liu, Ziqin Liao, Jie Pang, Yong He, Xuan Wei

“…In this study, a nondestructive detection method for strain degradation based on the fusion of hyperspectral technology and image texture features is presented. …”
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An improved lightweight tiny-person detection network based on YOLOv8: IYFVMNet by Fan Yang, Lihu Pan, Hongyan Cui, Linliang Zhang

“…This operation also reduces the computational cost by decreasing the amount of required feature map channels, while maintaining the effectiveness of the feature representation. (3) he Minimum Point Distance Intersection over Union loss function is employed to optimize bounding box detection during model training. (4) to construct the overall network structure, the Layer-wise Adaptive Momentum Pruning algorithm is used for thinning.ResultsExperiments on the TinyPerson dataset demonstrate that IYFVMNet achieves a 46.3% precision, 30% recall, 29.3% mAP50, and 11.8% mAP50-95.DiscussionThe model exhibits higher performance in terms of accuracy and efficiency when compared to other benchmark models, which demonstrates the effectiveness of the improved algorithm (e.g., YOLO-SGF, Guo-Net, TRC-YOLO) in small-object detection and provides a reference for future research.…”
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MIF-YOLO: An Enhanced YOLO with Multi-Source Image Fusion for Autonomous Dead Chicken Detection by Jiapan Li, Yan Zhang, Yong Zhang, Hongwei Shi, Xianfang Song, Chao Peng

“…Addressing the paucity of automated systems for the detection of dead poultry within large-scale agricultural settings, characterized by the onerous and time-consuming manual inspection processes, this study introduces an enhanced YOLO algorithm with multi-source image fusion (MIF-YOLO) for the autonomous identification of dead chicken. …”
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A synergistic approach for enhanced eye blink detection using wavelet analysis, autoencoding and Crow-Search optimized k-NN algorithm by M. Chandralekha, N. Priyadharshini Jayadurga, Thomas M. Chen, Mithileysh Sathiyanarayanan, Kasif Saleem, Mehmet A. Orgun

“…The k-NN model that has been optimized using the proposed method demonstrates significantly higher performance in the eye blink detection process in comparison to the deep learning models when equipped with decorous feature extraction and fine tuning. …”
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LS-YOLO: A Lightweight, Real-Time YOLO-Based Target Detection Algorithm for Autonomous Driving Under Adverse Environmental Conditions by Cheng Ju, Yuxin Chang, Yuansha Xie, Dina Li

“…To address these issues, a lightweight real-time object detection algorithm, LS-YOLO, is proposed. The LS-YOLO incorporates a MACA module to capture both global and local features, an SPDD module to reduce computational complexity, and a DR-Concat module to optimize feature fusion. …”
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An M-DeepSORT Algorithm for Pedestrian Detection and Tracking Based on Video Images – A Case Study in Ji-nan Subway Station by Wei ZHANG, Chuang ZHU, Yunchao QU, Guanhua LIU, Der-Horng LEE

“…Experimental results affirm the effectiveness of the proposed algorithm in detecting, tracking and statistically analysing subway station corridor passenger flow trajectories, demonstrating robust performance in diverse subway station scenarios.…”
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