Basic Introduction of New Energy Vehicles Structure and Research Progress on Fault Detection Methods of New Energy Vehicles by Ling Hao

“…Future research should refine the display of fault detection results to enhance maintenance efficiency.…”
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A Chelating Resin of EDTA-Type Modified Cross-Linking Polystyrene to Preconcentrate Trace Metals for Seawater Detection by Chao Li, Linna Duan, Mingchao Han, Hongwei He, Mengxiang Yuan, Hairong Wang

“…Compared with the conventional solvent method, the novel material and enrichment device have high preconcentration efficiency, strong anti-interference ability, and low cost and could be directly applied for routine seawater detection.…”
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A Deep Learning Approach to Identify Rock Bolts in Complex 3D Point Clouds of Underground Mines Captured Using Mobile Laser Scanners by Dibyayan Patra, Pasindu Ranasinghe, Bikram Banerjee, Simit Raval

“…Addressing these challenges, this paper proposes an approach termed <i>DeepBolt</i>, which employs a novel two-stage deep learning architecture specifically designed for handling severe class imbalance for the automatic and efficient identification of rock bolts in complex 3D point clouds. …”
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Studying the performance of YOLOv11 incorporating DHSA BRA and PPA modules in railway track fasteners defect detection by Chengwei Zhang, Jiawei Zhu, Yihao Ma, Qingmei Huang

“…The model also demonstrates competitive performance compared to other popular object detection algorithms, highlighting its potential to improve both detection accuracy and efficiency.…”
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YOLOv8-OCHD: A Lightweight Wood Surface Defect Detection Method Based on Improved YOLOv8 by Zuxing Chen, Junjie Feng, Xueyan Zhu, Bin Wang

“…To overcome the drawbacks of manual defect detection and the challenges of traditional visual inspection algorithms, such as high missed detection rates, slow detection speeds, and difficulties in deployment on embedded devices for detecting subtle wood surface defects, this study aims to improve the utilization efficiency of wood in enterprises. …”
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An Improved YOLOv8-Based Dense Pedestrian Detection Method with Multi-Scale Fusion and Linear Spatial Attention by Han Gong, Tian Li, Lijuan Wang, Shucheng Huang, Mingxing Li

“…Simultaneously, a multi-scale linear spatial attention module is designed to amplify features of visible parts of occluded pedestrians while suppressing interference from complex backgrounds. Secondly, a small-scale pedestrian detection head is introduced in the neck of the YOLOv8 network to enhance detection performance for diminutive pedestrians. …”
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DCA-YOLOv8: A Novel Framework Combined with AICI Loss Function for Coronary Artery Stenosis Detection by Hualin Duan, Sanli Yi, Yanyou Ren

“…In order to improve the accuracy and efficiency of detection, a new deep-learning technique based on a coronary artery stenosis detection framework (DCA-YOLOv8) is proposed in this paper. …”
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A deep Reinforcement learning-based robust Intrusion Detection System for securing IoMT Healthcare Networks by Jamshed Ali Shaikh, Chengliang Wang, Muhammad Wajeeh Us Sima, Muhammad Arshad, Muhammad Owais, Dina S. M. Hassan, Reem Alkanhel, Mohammed Saleh Ali Muthanna

“…The system integrates Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM) networks, and Reinforcement Learning (RL) techniques, namely Deep Q-Network (DQN) and Proximal Policy Optimization (PPO), to enhance the detection of evolving threats. The methodology begins with Enhanced Mutual Information Feature Selection (MIFS) to preprocess the CICIoMT2024 dataset, selecting the most relevant features while reducing noise and computational complexity. …”
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EMHANet: Lightweight Salient Object Detection for Remote Sensing Images via Edge-Aware Multiscale Feature Fusion by Qian Tang, Zhen Wang, Xuqi Wang, Shan-Wen Zhang

“…The network employs a coarse-to-fine strategy to accurately detect salient objects while maintaining efficiency. …”
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Acoustic Signal-Based Deep Learning Approach and Device for Detecting Interfacial Voids in Steel–Concrete Composite Structures by Wei Tian, Hang Yuan, Xinpeng You, Hehui Zheng, Bazhou Li, Chengming Peng

“…Developed tracked magnetic inspection robots can be applied to a variety of towering and complex confined areas, with real-time inspection efficiency as high as 0.1 m2/s. …”
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TMBO-AOD: Transparent Mask Background Optimization for Accurate Object Detection in Large-Scale Remote-Sensing Images by Tianyi Fu, Hongbin Dong, Benyi Yang, Baosong Deng

“…Recent advancements in deep-learning and computer vision technologies, coupled with the availability of large-scale remote-sensing image datasets, have accelerated the progress of remote-sensing object detection. However, large-scale remote-sensing images typically feature extensive and complex backgrounds with small and sparsely distributed objects, which pose significant challenges to detection performance. …”
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Research on Lightweight Algorithm Model for Precise Recognition and Detection of Outdoor Strawberries Based on Improved YOLOv5n by Xiaoman Cao, Peng Zhong, Yihao Huang, Mingtao Huang, Zhengyan Huang, Tianlong Zou, He Xing

“…The SPPELAN module is added as well to improve the model’s detection efficiency for small objects. The experimental results show that the detection accuracy of the improved model is 98.94%, the recall rate is 99.12%, the model volume is 53.22 MB, and the mAP value is 99.43%. …”
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A Constant False Alarm Rate Detection Method for Sonar Imagery Targets Based on Segmented Ordered Weighting by Wankai Na, Haisen Li, Jian Wang, Jiani Wen, Tianyao Xing, Yuxia Hou

“…Achieving reliable target detection in the field of sonar imagery represents a significant challenge due to the complex underwater interference patterns characterized by speckle noise, tunnel effects, and low-signal-to-noise ratio (SNR) environments. …”
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Infrared Small Target Detection Using Directional Derivative Correlation Filtering and a Relative Intensity Contrast Measure by Feng Xie, Dongsheng Yang, Yao Yang, Tao Wang, Kai Zhang

“…Moreover, the framework maintains low computational complexity, achieving a favorable balance between detection accuracy and efficiency, thereby demonstrating promising potential for deployment in practical IRST scenarios.…”
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Detecting drug transfers via the drop-off method: A supervised model approach using AIS data by Britt van Leeuwen, Maike Nutzel

“…Unlike existing research, primarily employing unsupervised methods, we propose a supervised model specifically tailored to this illicit activity, with a particular emphasis on its application to fishing vessels.Our model significantly reduces the number of data points requiring classification by the observer by 70% , thereby enhancing the efficiency of the drop-off detection process. By employing a Long Short-Term Memory (LSTM) model, our approach demonstrates a change from traditional methods and offers advantages in capturing complex temporal patterns inherent in ‘drop-off’ activities. …”
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Enhancing Real-Time Aerial Image Object Detection with High-Frequency Feature Learning and Context-Aware Fusion by Xin Ge, Liping Qi, Qingsen Yan, Jinqiu Sun, Yu Zhu, Yanning Zhang

“…Aerial image object detection faces significant challenges due to notable scale variations, numerous small objects, complex backgrounds, illumination variability, motion blur, and densely overlapping objects, placing stringent demands on both accuracy and real-time performance. …”
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Automated Digitization Approach for Road Intersections Mapping: Leveraging Azimuth and Curve Detection from Geo-Spatial Data by Ahmad M. Senousi, Wael Ahmed, Xintao Liu, Walid Darwish

“…Unlike conventional approaches that only detect intersection positions, our method systematically reconstructs complete intersection geometries while maintaining topological consistency. …”
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Scalable Detection of Underground Water Leaks in Dense Urban Environments Using L-Band SAR and Machine Learning by E. Ali, E. Ali, L. Xie, A. Sani-Mohammed, W. Xu, T. Zayed

“…Underground water leaks in urban networks result in significant resource loss, infrastructure degradation, and environmental damage&mdash;challenges that are particularly acute in high-density cities like Hong Kong, where aging and complex infrastructure complicates detection. Traditional methods such as acoustic sensing and manual inspections often fall short in efficiency and scalability. …”
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Research on a Wear Defect Detection Method for a Switch Sliding Baseplate Based on Improved Yolov5 by Qing Jiang, Ruipeng Gao, Yan Zhao, Wenzhen Yu, Zhuofan Dang, Shiyi Deng

“…Wear defects occurring on the switch sliding baseplate can give rise to issues such as delayed switch operation, inflexible switching, or even complete failure, thereby escalating the risk of train derailment. Consequently, the detection of wear defects on the switch sliding baseplate is of paramount importance for enhancing traffic efficiency and guaranteeing the safety of train switching operations. …”
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Designing and analysis of flexible four legged-loaded metamaterial absorber sensor for permittivity detection of a solid substrate by Shihabun Sakib, Mohammad Tariqul Islam, Ahasanul Hoque, Abdulmajeed M. Alenezi, Mohamed S. Soliman, Haitham Alsaif

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