LE-YOLO: A Lightweight and Enhanced Algorithm for Detecting Surface Defects on Particleboard by Chao He, Yongkang Kang, Anning Ding, Wei Jia, Huaqiong Duo

“…Compared with other models, the proposed approach not only improved detection precision but also effectively reduced model complexity, achieving a lightweight and efficient detection framework.…”
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Qseek: A data-driven Framework for Automated Earthquake Detection, Localization and Characterization by Marius Isken, Sebastian Heimann, Peter Niemz, Jannes Münchmeyer, Simone Cesca, Hannes Vasyura-Bathke, Torsten Dahm

“…The resolution of the search volume is iteratively refined toward the seismic source location; this strategy facilitates an efficient, fast, and accurate search. We present a user-friendly and high-performance open-source software framework based on established frameworks, featuring event detection in layered 1D and complex 3D velocity models and event feature extraction capabilities, such as moment and local magnitude calculation from peak ground motions. …”
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Detection and Recognition of Underwater Acoustic Communication Signal Under Ocean Background Noise by Mengyi Li, Jilong Li, Haihong Feng

“…Non-cooperative underwater acoustic signal detection and recognition technologies occupy an important position in the marine communication environment. …”
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Vision transformer embedded video anomaly detection using attention driven recurrence by Ummay Maria Muna, Shanta Biswas, Syed Abu Ammar Muhammad Zarif, Philip Jefferson Deori, Tauseef Tajwar, Swakkhar Shatabda

“…Automated video anomaly detection (VAD) is a challenging task due to its context-dependent and sporadic nature. …”
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Blockage detection in pipelines based on linear frequency modulated acoustic reflection method by Haiyuan Yao, Dan Li, Yan Li, Bo Yang, Yang Meng

“…This study proposes a novel acoustic-based structural health monitoring system integrating linear frequency modulated (LFM) signals with adaptive matched filtering, specifically designed for early blockage detection in complex pipeline networks, including those in built environments. …”
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A Comprehensive Study On Underwater Object Detection Using Deep Neural Networks by K. Samanth, Ramyashree Ramyashree, B. N. Anoop, S. Raghavendra

“…Identifying and removing submerged debris is challenging due to poor visibility, complex water conditions, and the inefficiency of traditional manual approaches. …”
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Classifying IoT Botnet Attacks With Kolmogorov-Arnold Networks: A Comparative Analysis of Architectural Variations by Phuc Hao do, Tran Duc Le, Truong Duy Dinh, van Dai Pham

“…The Original-KAN variant, in particular, excelled in capturing complex, non-linear patterns inherent in IoT botnet traffic, achieving higher accuracy and faster convergence rates. …”
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FSDN-DETR: Enhancing Fuzzy Systems Adapter with DeNoising Anchor Boxes for Transfer Learning in Small Object Detection by Zhijie Li, Jiahui Zhang, Yingjie Zhang, Dawei Yan, Xing Zhang, Marcin Woźniak, Wei Dong

“…This approach achieves a balance between computational efficiency for medium-resolution images and the accuracy required for small object detection. …”
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An Enhanced and Lightweight YOLOv8-Based Model for Accurate Rice Pest Detection by Guisuo Liu, Juxing Di, Qing Wang, Yan Zhao, Yang Yang

“…The results validate that the proposed model is not only effective and efficient but also robust and lightweight, making it a promising solution for rice pest detection and offering valuable support for pest management in precision agriculture.…”
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A Secure and Robust Machine Learning Model for Intrusion Detection in Internet of Vehicles by Pradeep Kumar Tiwari, Shiv Prakash, Animesh Tripathi, Tiansheng Yang, Rajkumar Singh Rathore, Manish Aggarwal, Narendra Kumar Shukla

“…In this paper, we proposed a fine tree-based model to study the complex behavior of network traffic inside the IoV to detect and classify anomalies for securing the IoV. …”
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Dynamic response and discrimination of gaseous sarin using a boron‐difluoride complex film‐based fluorescence sensor by Zhijie Zhou, Lei Zhang, Lingya Peng, Yingjie Li, Xiaolin Zhu, Yidi Wu, Zebiao Qiu, Gang He, Molin Qin, Haonan Peng, Yu Fang

“…Abstract This study presents a novel boron‐difluoride complex‐based fluorescent nanofilm sensor capable of detecting sarin vapors in the environment by reporting an output fluorescence signal. …”
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A small underwater object detection model with enhanced feature extraction and fusion by Tao Li, Yijin Gang, Sumin Li, Yizi Shang

“…Advancements in deep learning have led to the development of many efficient detection techniques. However, the complexity of the underwater environment, limited information available from small objects, and constrained computational resources make small object detection challenging. …”
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Lightweight Apple Leaf Disease Detection Algorithm Based on Improved YOLOv8 by LUO Youlu, PAN Yonghao, XIA Shunxing, TAO Youzhi

“…To reduce the incidence of apple diseases and increase fruit yield, developing efficient and fast apple leaf disease detection technology is of great significance. …”
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PCPE-YOLO with a lightweight dynamically reconfigurable backbone for small object detection by Weijia Chen, Jiaming Liu, Tong Liu, Yaoming Zhuang

“…Abstract In the domain of object detection, small object detection remains a pressing challenge, as existing approaches often suffer from limited accuracy, high model complexity, and difficulty meeting lightweight deployment requirements. …”
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An improved method of AUD-YOLO for surface damage detection of wind turbine blades by Li Zou, Anqi Chen, Xinhua Yang, Yibo Sun

“…Abstract The detection of wind turbine blades (WTBs) damage is crucial for improving power generation efficiency and extending the lifespan of turbines. …”
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Detection of Pear Quality Using Hyperspectral Imaging Technology and Machine Learning Analysis by Zishen Zhang, Hong Cheng, Meiyu Chen, Lixin Zhang, Yudou Cheng, Wenjuan Geng, Junfeng Guan

“…In summary, the combination of HSI and machine learning models enabled an efficient, rapid, and non-destructive detection of pear quality and provided a practical value for quality control and the commercial processing of pears.…”
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HGLFNet: Hybrid Global Semantic and Local Detail Feature Network for Lane Detection by Lei Ding, Chunhui Tang, Yi Fang

“…The experimental results comprehensively demonstrate that HGLFNet surpasses the existing state-of-the-art techniques in both accuracy and efficiency, providing a novel and effective solution for lane detection in complex scenarios and showing significant potential in practical applications.…”
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YOLO-MES: An Effective Lightweight Underwater Garbage Detection Scheme for Marine Ecosystems by Chengxu Huang, Wenyuan Zhang, Beitian Zheng, Jiahao Li, Bochen Xie, Ruisi Nan, Zongming Tan, Baohua Tan, Neal N. Xiong

“…Experimental results indicate that YOLO-MES achieves 95.8% accuracy on the dataset, while reducing model size and computational complexity by 64% and 67%, respectively. Compared to existing mainstream detection algorithms, YOLO-MES offers significant advantages in lightweight design and computational efficiency, providing a practical and deployable solution for underwater target detection on mobile devices.…”
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Experimental Demonstration of 16-QAM DD-SEFDM With Cascaded BPSK Iterative Detection by Jun Huang, Qi Sui, Zhaohui Li, Fei Ji

“…To simplify the complexity of a spectrally efficient frequency-division multiplexing (SEFDM) system, cascaded binary-phase-shift-keying iterative detection (CBID) is proposed for square <inline-formula> <tex-math notation="LaTeX">$M$</tex-math></inline-formula>-ary quadrature-amplitude-modulation (M-QAM) SEFDM as the first decoding stage, in conjunction with a fixed sphere decoder (FSD). …”
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Enhanced anomaly traffic detection framework using BiGAN and contrastive learning by Haoran Yu, Wenchuan Yang, Baojiang Cui, Runqi Sui, Xuedong Wu

“…However, existing methods face many challenges when processing complex high-dimensional traffic data. Especially in dealing with redundant features, data sparsity and nonlinear features, traditional methods often suffer from high computational complexity and low detection efficiency. …”
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