Comparative evaluation of voltage conversion and encoder pulse detection methods for controlling a model high-bay warehouse by Anas Abu Al-Hija’a, B. J. Szekeres, M. Andó

“…The presented evaluation enhances control strategies for industrial automation, emphasizing efficient voltage conversion and precise encoder pulse detection to enhance system performance and reliability, laying the groundwork for future advancements in remote control capabilities and complex manufacturing systems.…”
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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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Exploring the Application of Large Language Models Based AI Agents in Leakage Detection of Natural Gas Valve Chambers by Qian Wei, Hongjun Sun, Yin Xu, Zisheng Pang, Feixiang Gao

“…The traditional detection methods highly depend on manpower with large workload and are prone to missed and false alarms, which seriously affects the efficiency and safety of oil and gas production and transportation. …”
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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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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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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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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—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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FASTSeg3D: A Fast, Efficient, and Adaptive Ground Filtering Algorithm for 3D Point Clouds in Mobile Sensing Applications by Daniel Ayo Oladele, Elisha Didam Markus, Adnan M. Abu-Mahfouz

“…Background: Accurate ground segmentation in 3D point clouds is critical for robotic perception, enabling robust navigation, object detection, and environmental mapping. However, existing methods struggle with over-segmentation, under-segmentation, and computational inefficiency, particularly in dynamic or complex 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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Federated learning with LSTM for intrusion detection in IoT-based wireless sensor networks: a multi-dataset analysis by Raja Waseem Anwar, Mohammad Abrar, Abdu Salam, Faizan Ullah

“…Traditional centralized intrusion detection systems (IDS) face significant challenges in data privacy, computational efficiency, and scalability, particularly in resource-constrained IoT environments. …”
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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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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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Integrating Stride Attention and Cross-Modality Fusion for UAV-Based Detection of Drought, Pest, and Disease Stress in Croplands by Yan Li, Yaze Wu, Wuxiong Wang, Huiyu Jin, Xiaohan Wu, Jinyuan Liu, Chen Hu, Chunli Lv

“…This study demonstrates that the integration of lightweight attention mechanisms with multimodal UAV remote sensing imagery enables efficient, accurate, and scalable agricultural disaster detection under complex field conditions.…”
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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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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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A Lightweight YOLOv8s Algorithm for Ceiling Fan Blade Defect Detection With Optimized Pruning and Knowledge Distillation by Qinyuan Huang, Chen Fan, Yuqi Sun, Jiaxiong Huang, Wengziyang Jiang

“…Detecting these surface defects is crucial; however, accurate and rapid detection typically involves complex machine vision algorithms, such as You Only Look Once (YOLO) networks, that require considerable computing resources, which contradicts the industry’s preference for simpler algorithms that can be deployed using low-cost computing power. …”
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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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