Detecting seasonal differences in high-frequency site response using κ0 by Annabel Händel, Marco Pilz, Luca C. Malatesta, David Litwin, Fabrice Cotton

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Real-time classroom student behavior detection based on improved YOLOv8s by Xiaojing Sheng, Suqiang Li, Sixian Chan

“…With the rapid advancement of behavior detection technology, identifying classroom behaviors of students is becoming increasingly common in educational settings. …”
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Spatiotemporal Correlation Based Fault-Tolerant Event Detection in Wireless Sensor Networks by Kezhong Liu, Yang Zhuang, Zhibo Wang, Jie Ma

“…Reliable event detection is one of the most important objectives in wireless sensor networks (WSNs), especially in the presence of faulty nodes. …”
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SPBA-Net point cloud object detection with sparse attention and box aligning by Haojie Sha, Qingrui Gao, Hao Zeng, Kai Li, Wang Li, Xuande Zhang, Xiaohui Wang

“…Abstract Object detection in point clouds is essential for various applications, including autonomous navigation, household robots, and augmented/virtual reality. …”
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OFPoint: Real-Time Keypoint Detection for Optical Flow Tracking in Visual Odometry by Yifei Wang, Libo Sun, Wenhu Qin

“…Visual odometry (VO), including keypoint detection, correspondence establishment, and pose estimation, is a crucial technique for determining motion in machine vision, with significant applications in augmented reality (AR), autonomous driving, and visual simultaneous localization and mapping (SLAM). …”
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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

“…The AKConv convolution operation is employed to adaptively adjust the size of convolutions, further enhancing local feature capturing. Additionally, a lightweight network design is implemented, establishing G-Head (Ghost-Head) as the detection head to optimize the issue of feature redundancy. …”
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Lightweight construction safety behavior detection model based on improved YOLOv8 by Kan Huang, Mideth B. Abisado

“…At the same time, the receptive field is expanded by combining the Receptive Field Block (RFB) module, the ability to capture multi-scale features is enhanced, and the Global Attention Mechanism (GAM)-Attention mechanism is introduced to enhance the recognition ability of local features. Through experimental results, the improved YOLOv8 model performed excellently in detecting five common unsafe behaviors of construction workers, with an mAP of 0.86, a precision of 0.84, a recall rate of 0.87, an F1 value of 0.85, and an IoU of 0.8, which are significantly better than traditional methods. …”
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Infrared small target detection algorithm with U-shaped multiscale transformer network by DUAN Peipei, ZHANG Yan, LUO Mingshi, YAN Xiaoying

“…This accomplishes pixel-level segmentation of infrared small targets, fulfilling the purpose of target detection. Experiments demonstrate in infrared sequence image dim and small aircraft target detection and tracking data set, even when applied to infrared images with complex background and noisy, our method outperforms the state-of-the-art detection methods. …”
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EEG-DGRN: dynamic graph representation network for subject-independent ERP detection by Jiabin Zhu, Xuanyu Jin, Yuhang Ming, Wanzeng Kong

“…Then, considering the local and global topology structure, a dual-branch graph pooling module is employed to prune features from different granularity. …”
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Detecting Millimetric Slow Slip Events Along the North Anatolian Fault With GNSS by Alpay Özdemir, Jorge Jara, Uğur Doğan, Romain Jolivet, Ziyadin Çakir, Jean‐Mathieu Nocquet, Semih Ergintav, Roger Bilham

“…Along the central section of the North Anatolian Fault, we apply a Multichannel Singular Spectrum Analysis (MSSA) on GNSS time series of ground motion to detect a Mw 4.8 ± 0.08 shallow SSE (2–5 km depth) lasting for 26 ± 5 days, in agreement with local creepmeter observations. …”
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Magnetic Microdevices for MRI-Based Detection of SARS-CoV-2 Viruses by Lamar O. Mair, Olivia Hale, Sahar Jafari, Cheng Chen, Oleg Udalov, Roland Probst, Ittai Baum, Anjana Hevaganinge, Elaine Yi Wang, Olga C. Rodriguez, Christopher Albanese, Stanley T. Fricke, Irving N. Weinberg

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Attribute grouping-based categorical outlier detection using causal coupling weight by Yijing Song, Jianying Liu, Jifu Zhang

“…Firstly, according to the local and global correlation, all attributes are automatically divided into several groups, and all attributes in each group have a high correlation or association. …”
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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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YOLO-LPSS: A Lightweight and Precise Detection Model for Small Sea Ships by Liran Shen, Tianchun Gao, Qingbo Yin

“…We propose YOLO-LPSS, a novel model designed to significantly improve small ship detection accuracy with low computation cost. The characteristics of YOLO-LPSS are as follows: (1) Strengthening the backbone’s ability to extract and emphasize features relevant to small ship objects, particularly in semantic-rich layers. (2) A sophisticated, learnable method for up-sampling processes is employed, taking into account both deep image information and semantic information. (3) Introducing a post-processing mechanism in the final output of the resampling process to restore the missing local region features in the high-resolution feature map and capture the global-dependence features. …”
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Deep-learning-based detection of underwater fluids in multiple multibeam echosounder data by Tyméa Perret, Gilles Le Chenadec, Arnaud Gaillot, Yoann Ladroit, Stéphanie Dupré

“…The results demonstrate first that this method surpasses current machine learning techniques, such as Haar-Local Binary Pattern Cascade. Additionally, we thoroughly analyzed the composition of the training dataset and evaluated the detection performance based on various training configurations. …”
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Detection of AI-Generated Texts: A Bi-LSTM and Attention-Based Approach by John Blake, Abu Saleh Musa Miah, Krzysztof Kredens, Jungpil Shin

“…The initial module extracts local contextual features using convolutional layers, followed by Bi-LSTM layers that capture long-term dependencies from past and future sequences. …”
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A texture enhanced attention model for defect detection in thermal protection materials by Jialin Song, Zhaoba Wang, Kailiang Xue, Youxing Chen, Guodong Guo, Maozhen Li, Asoke K. Nandi

“…And we propose an innovative texture-enhanced attention defect detection (TADD) model that enables accurate, efficient, and real-time defect detection. …”
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Multispectral Target Detection Based on Deep Feature Fusion of Visible and Infrared Modalities by Yongsheng Zhao, Yuxing Gao, Xu Yang, Luyang Yang

“…Multispectral detection leverages visible and infrared imaging to improve detection performance in complex environments. …”
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Deepfake Detection Method Integrating Multiple Parameter-Efficient Fine-Tuning Techniques by ZHANG Yiwen, CAI Manchun, CHEN Yonghao, ZHU Yi, YAO Lifeng

“…Concurrently, it introduces a parallel structure incorporating convolutional adapters to capture local texture information, enhancing the model’s adaptability in deepfake detection tasks. …”
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Cybersecurity of smart grids: Comparison of machine learning approaches training for anomaly detection by S. V. Kochergin, S. V. Artemova, A. A. Bakaev, E. S. Mityakov, Zh. G. Vegera, E. A. Maksimova

“…The comparison of machine learning methods reveals the varying effectiveness of anomaly detection methods used to detect cyber threats and deviations in electrical systems. …”
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