A Benchmark Review of YOLO Algorithm Developments for Object Detection by Zhengmao Hua, Kaviya Aranganadin, Cheng-Cheng Yeh, Xinhe Hai, Chen-Yun Huang, Tsan-Chuen Leung, Hua-Yi Hsu, Yung-Chiang Lan, Ming-Chieh Lin

“…You Only Look Once (YOLO) has established itself as a prominent object detection framework due to its excellent balance between speed and accuracy. …”
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Lightweight detection algorithms for small targets on unmanned mining trucks by Shuoqi CHENG, Yilihamu·YAERMAIMAITI, Lirong XIE, Xiyu LI, Ying MA

“…Accurate target category detection is a prerequisite for obstacle avoidance decisions, and model lightweighting facilitates deployment in resource-limited conditions. …”
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Fast detection method for radionuclides based on Sequential Bayesian approach by WAN Linjian, ZHANG Xuan, ZHANG Chunlei, HUANG Jianwei, LIU Jiacheng, ZHANG Xiaole, LI Dehong, YANG Zhijun

“…Finally, experimental verifications were conducted on the feasibility, detection performance, and universality of the method by placing a set of standard point sources at different distances from the front of a LaBr3(Ce) detection system in both low and natural radiation background environments. …”
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A Self-Adaptive Particle Swarm Optimization Based Multiple Source Localization Algorithm in Binary Sensor Networks by Long Cheng, Yan Wang, Shuai Li

“…Then the maximum likelihood estimator is employed to establish the objective function which is used to estimate the location of sources. …”
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Detection of water surface targets based on improved Deformable DETR by Pengjiu WANG, Junbin Gong, Wei LUO, Xiao HUANG, Junjie GUO

“…Objective With technological advancements and the increasing demand for water resource exploration, water surface target detection plays a crucial role in various applications, such as ship navigation and maritime safety. …”
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Multivariate GWAS analysis reveals loci associated with liver functions in continental African populations. by Chisom Soremekun, Tafadzwa Machipisa, Opeyemi Soremekun, Fraser Pirie, Nashiru Oyekanmi, Ayesha A Motala, Tinashe Chikowore, Segun Fatumo

“…<h4>Conclusions</h4>Using multivariate GWAS method improves the power to detect novel genotype-phenotype associations for liver functions not found with the standard univariate GWAS in the same dataset.…”
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A rapid and accurate method for Helicobacter pylori detection via integrating LAMP assay with CRISPR/Cas12b detection by one-step in one-pot by Yeqian Zhang, Tao Liu, Puhua Zhang, Bo Ni, Xingang Wang, Long Bai, Wei Sun, Yujing Guan, Xiang Xia, Hui Cao, Jiayi Gu

“…Conventional diagnostic methods, such as PCR and culture, require specialized equipment and expertise, limiting their applicability in resource-limited settings. There is a pressing need for a rapid, cost-effective, and user-friendly diagnostic platform for HP detection, particularly in point-of-care settings.MethodsWe developed an integrated detection platform combining loop-mediated isothermal amplification (LAMP) with the CRISPR/Cas12b system in a single, one-step, one-pot reaction. …”
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Joint Multifractal Analysis and Source Testing of River Level Records Based on Multifractal Detrended Cross-Correlation Analysis by Liang Wu, Manling Wang, Tongzhou Zhao

“…It is important for the detection of change in multifractality in space. Besides, the cross-correlations in two analyzed series make the analysis of sources of joint multifractality difficult. …”
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Algorithms for Automatic Detection and Location of Infrasound Events in the PSDL System by Asming Vladimir Ernestovich, Fedorov Andrey Viktorovich

“…An algorithm for detecting infrasound signals by calculating the cross-correlation function between records of individual sensors in a array is described. …”
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Code vulnerability detection method based on graph neural network by Hao CHEN, Ping YI

“…The schemes of using neural networks for vulnerability detection are mostly based on traditional natural language processing ideas, processing the code as array samples and ignoring the structural features in the code, which may omit possible vulnerabilities.A code vulnerability detection method based on graph neural network was proposed, which realized function-level code vulnerability detection through the control flow graph feature of the intermediate language.Firstly, the source code was compiled into an intermediate representation, and then the control flow graph containing structural information was extracted.At the same time, the word vector embedding algorithm was used to initialize the vector of basic block to extract the code semantic information.Then both of above were spliced to generate the graph structure sample data.The multilayer graph neural network model was trained and tested on graph structure data features.The open source vulnerability sample data set was used to generate test data to evaluate the method proposed.The results show that the method effectively improves the vulnerability detection ability.…”
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Detection, Parameter Estimation and Direction Finding of Periodic Pulse Signals by V. B. Manelis, I. S. Faustov, V. A. Kozmin

“…Simple-to-implement algorithms for detecting periodic pulse signals, evaluating their parameters, and direction finding of the source have been developed. …”
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Performance Analysis of Diabetes Detection Using Machine Learning Classifiers by Hung Huynh, Liu Hui, Ngoc Han Nguyen, Ruixuan Qiao

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Exploring RNA cargo in extracellular vesicles for pleural mesothelioma detection by Agnieszka Kraft, Michaela B. Kirschner, Vanessa Orlowski, Manuel Ronner, Caroline Bodmer, Valentina Boeva, Isabelle Opitz, Mayura Meerang

“…Conclusions This is the first study to characterize the transcriptomic profile of EVs secreted by PM primary cell cultures, demonstrating their potential as biomarker source for early detection. Further investigation of the functional role of PM-EVs will provide new insights into disease biology and therapeutic avenues.…”
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Toward global rooftop PV detection with Deep Active Learning by Matthias Zech, Hendrik-Pieter Tetens, Joseph Ranalli

“…It is crucial to know the location of rooftop PV systems to monitor the regional progress toward sustainable societies and to ensure the integration of decentralized energy resources into the electricity grid. However, locations of PV are often unknown, which is why a large number of studies have proposed variants of Deep Learning to detect PV panels in remote sensing data using supervised Deep Learning. …”
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Schizophrenia Detection and Classification: A Systematic Review of the Last Decade by Arghyasree Saha, Seungmin Park, Zong Woo Geem, Pawan Kumar Singh

“…The SZ symptoms can significantly impair daily functioning, underscoring the need for advanced diagnostic tools. …”
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A Lightweight Citrus Object Detection Method in Complex Environments by Qiurong Lv, Fuchun Sun, Yuechao Bian, Haorong Wu, Xiaoxiao Li, Xin Li, Jie Zhou

“…Aiming at the limitations of current citrus detection methods in complex orchard environments, especially the problems of poor model adaptability and high computational complexity under different lighting, multiple occlusions, and dense fruit conditions, this study proposes an improved citrus detection model, YOLO-PBGM, based on You Only Look Once v7 (YOLOv7). …”
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Radar Detection Simulation by Digital Twins of Target and Antenna System by A. S. Grigoriev, A. A. Kazantsev, A. M. Terentyev, B. S. Stavtsev

“…The signal-to-noise dynamic dependence of the given radar system, space object, and observation scenario, presented by their digital models, was calculated. The function of detection probability density was calculated, which demonstrated an insufficient detection capacity of a radar system in the case of observation of such type of objects.Conclusion. …”
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Improved CSW-YOLO Model for Bitter Melon Phenotype Detection by Haobin Xu, Xianhua Zhang, Weilin Shen, Zhiqiang Lin, Shuang Liu, Qi Jia, Honglong Li, Jingyuan Zheng, Fenglin Zhong

“…The diversity of bitter melon shapes has a direct impact on its market acceptance and consumer preferences, making precise identification of bitter melon germplasm resources crucial for breeding work. To address the limitations of time-consuming and less accurate traditional manual identification methods, there is a need to enhance the automation and intelligence of bitter melon phenotype detection. …”
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Distribution and functional significance of KLF15 in mouse cerebellum by Dan Li, Shuijing Cao, Yanrong Chen, Yueyan Liu, Kugeng Huo, Zhuangqi Shi, Shuxin Han, Liecheng Wang

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A lightweight object detection approach based on edge computing for mining industry by Muhammad Wahab Hanif, Zhanli Li, Zhenhua Yu, Rehmat Bashir

“…These enhancements enable more accurate and efficient detection in resource‐constrained edge environments, contributing to safer and more reliable monitoring in coal mining operations.…”
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