Enhanced YOLO and Scanning Portal System for Vehicle Component Detection by Feng Ye, Mingzhe Yuan, Chen Luo, Shuo Li, Duotao Pan, Wenhong Wang, Feidao Cao, Diwen Chen

“…The system consists of a scanning portal system and an improved YOLOv12-based detection algorithm which captures images of automotive parts passing through the scanning portal in real time. …”
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River floating object detection with transformer model in real time by Chong Zhang, Jie Yue, Jianglong Fu, Shouluan Wu

“…Building upon this foundation, we introduce the LR-DETR, a lightweight evolution of RT-DETR for river floating object detection. This model incorporates the High-level Screening-feature Path Aggregation Network (HS-PAN), which refines feature fusion through a novel bottom-up fusion path, significantly enhancing its expressive power. …”
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LDoS attack detection method based on traffic classification prediction by Liang Liu, Yue Yin, Zhijun Wu, Qingbo Pan, Meng Yue

“…The experimental results show that the global LDoS attack traffic detection method based on the Hurst index and GBDT algorithm achieves better detection results under different attack rates.…”
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ECG Paper Digitization and R Peaks Detection Using FFT by Ibraheam Fathail, Vaishali D. Bhagile

“…One of the most essential tools for detecting heart problems is the electrocardiogram (ECG). …”
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The analysis of fraud detection in financial market under machine learning by Jing Jin, Yongqing Zhang

“…Therefore, this paper proposes a financial fraud detection model based on Stacking ensemble learning algorithm, which integrates many basic learners such as logical regression (LR), decision tree (DT), random forest (RF), Gradient Boosting Tree (GBT), support vector machine (SVM) and neural network (NN), and introduces feature importance weighting and dynamic weight adjustment mechanism to improve the model performance. …”
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Enhancing Online Security: A Novel Machine Learning Framework for Robust Detection of Known and Unknown Malicious URLs by Shiyun Li, Omar Dib

“…The resulting malicious URL detection system (MUDS) combines supervised machine learning techniques, tree-based algorithms, and advanced data preprocessing, achieving a high detection accuracy of 96.83% for known MURLs. …”
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Myocarditis Detection Using Proximal Policy Optimization and Mutual Learning by Asadi Srinivasulu, Sivaram Rajeyyagari

“…The model employs multiple convolutional neural networks (CNNs) to extract feature vectors from images for classification. To address class imbalance, a proximal policy optimization (PPO)-based algorithm is utilized, significantly improving the training process by preventing abrupt policy shifts and stabilizing them. …”
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Broiler Behavior Detection and Tracking Method Based on Lightweight Transformer by Haixia Qi, Zihong Chen, Guangsheng Liang, Riyao Chen, Jinzhuo Jiang, Xiwen Luo

“…The FasterNet network based on partial convolution (PConv) was used to replace the Resnet18 backbone network to reduce the computational complexity of the model and to improve the speed of model detection. In addition, we propose a new cross-scale feature fusion network to optimize the neck network of the original model. …”
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Detection of DRFM Deception Jamming Based on Diagonal Integral Bispectrum by Dianxing Sun, Ao Li, Hao Ding, Jifeng Wei

“…Simulations and experimental results show that the correct detection rate reaches 92% at a jamming-to-signal ratio (JSR) and SNR of 0 dB, validating the effectiveness of the algorithm.…”
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Application of a Texture Appearance Model for Segmentation of Lung Nodules on Computed Tomography of the Chest by F. Shariaty, V. A. Pavlov, S. V. Zavjalov, M. Orooji, T. M. Pervunina

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Optimizing micro cold storage for detecting stale food and fruits by Arun Sreelekha, Amit Wagle Shivali, Nambiar Prahas, Panalkar Pratham, Ekka Prince, Kumar Vaibhav, Dhiman Harsh, Roy Anindita

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Detection method for dangerous behaviors of underground coal mine personnel by ZHANG Xuhui, YU Henghan, DU Yuyang, YANG Wenjuan, ZHAO Yihui, WAN Jicheng, WANG Yanqun, ZHAO Dian, TANG Duwei

“…Existing object detection technologies face challenges when applied to underground personnel behavior detection, as complex working conditions, equipment occlusion, dense targets, and dust interference often lead to inaccurate feature extraction and undefined behavior classifications. …”
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Prediction of Early Diagnosis in Ovarian Cancer Patients Using Machine Learning Approaches with Boruta and Advanced Feature Selection by Tuğçe Öznacar, Tunç Güler

“…Conclusions: This study highlights the importance of choosing appropriate machine learning algorithms and feature selection techniques for ovarian cancer diagnosis. …”
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Evaluating the performance of pixel-based and object-based multidimensional clustering algorithms for automated surface water mapping by Bohao Li, Kai Liu, Ming Wang, Yanfang Wang, Linmei Zhuang, Weihua Zhu, Chenxia Li, Linhao Zhang, Yanan Chen

“…The results show that pixel-based hierarchical clustering, which uses the optimal feature combination of B8, the NDWI, and the MBWI, is the algorithm with the best overall performance, with kappa coefficients exceeding 0.9 in each scene. …”
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Enhancing DDoS Attack Classification through SDN and Machine Learning: A Feature Ranking Analysis by Aymen AlAwadi, Kawthar Rasoul ALesawi

“…We reduced the feature up to 5 effective features without compromising the classification accuracy. …”
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Hybrid Optimized Feature Selection and Deep Learning Method for Emotion Recognition That Uses EEG Data by asmaa Bashar Hmaza, Rajaa K. Hasoun

“…This study incorporates the concepts of the PSO algorithm into a feature selection and deep learning model by using LSTM to enhance EEG emotion identification. …”
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Design of Jitter Compensation Algorithm for Robot Vision Based on Optical Flow and Kalman Filter by B. R. Wang, Y. L. Jin, D. L. Shao, Y. Xu

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Region-wise landmarks-based feature extraction employing SIFT, SURF, and ORB feature descriptors to recognize Monozygotic twins from 2D/3D Facial Images [version 2; peer review: 2... by Srikanth Prabhu, Vinod Nayak, Aparna Jayakala, Krishna Prakasha K, Gangothri Sanil

“…Methods This study explores face recognition system for monozygotic twins utilizing three widely recognized feature descriptor algorithms: Scale-Invariant Feature Transform (SIFT), Speeded-Up Robust Features (SURF), and Oriented Fast and Rotated BRIEF (ORB)—with region-specific facial landmarks. …”
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Multi-Scale Feature Mixed Attention Network for Cloud and Snow Segmentation in Remote Sensing Images by Liling Zhao, Junyu Chen, Zichen Liao, Feng Shi

“…The framework integrates three key components: (1) a Multi-scale Pooling Feature Perception Module to capture multi-level structural features, (2) a Bilateral Feature Mixed Attention Module that enhances boundary detection through spatial-channel attention, and (3) a Multi-scale Feature Convolution Fusion Module to reduce edge blurring. …”
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Development of an explainable machine learning model for Alzheimer’s disease prediction using clinical and behavioural features by Rajkumar Govindarajan, K. Thirunadanasikamani, Komal Kumar Napa, S. Sathya, J. Senthil Murugan, K. G. Chandi Priya

“…This method offers a practical tool for clinicians and researchers to support early diagnosis and personalized risk assessment of AD, thus aiding in timely and informed clinical decision-making.Accurate Prediction: Gradient Boosting model achieved 93.9 % accuracy for early Alzheimer’s detection.Explainability: SHAP values provided interpretable insights into key clinical features.Clinical Tool: A Streamlit-based web app enabled real-time, explainable predictions for users.…”
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