RpiBeh offers a versatile open source solution for rodent behavior tracking and closed loop interventions by Yiqi Sun, Jie Zhang, Qianyun Wang, Jianguang Ni

“…Existing commercial systems are costly and inflexible for customization, while current open-source tools are often lack of real-time functionality and suffer from steep learning curve. …”
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Randomization-Driven Hybrid Deep Learning for Diabetic Retinopathy Detection by A. M. Mutawa, G. R. Hemalakshmi, N. B. Prakash, M. Murugappan

“…This study pioneers an innovative framework, using Multi-Scale Discriminative Robust Local Binary Pattern (MS-DRLBP) features, combined with a hybrid Convolutional Neural Network-Radial Basis Function (CNN-RBF) classifier, to enhance the detection of DR. …”
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Optimized decomposition and identification method for multiple power quality disturbances by Wang Zhaoqing, Chang Yanzhao, Chen Jianlei, Bao Weiyu

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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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Are Your Kidneys Ok? Detect Early to Protect Kidney Health by Joseph A. Vassalotti, Anna Francis, Augusto Cesar Soares Dos Santos Jr, Ricardo Correa-Rotter, Dina Abdellatif, Li-Li Hsiao, Stefanos Roumeliotis, Agnes Haris, Latha A. Kumaraswami, Siu-Fai Lui, Alessandro Balducci, Vassilios Liakopoulos

“…using serum creatinine to estimate kidney function and urine albumin to assess for kidney and endothelial damage. …”
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MDV ClimEx: An open-source tool for exploring climate anomalies in the McMurdo Dry Valleys of Antarctica by Renée F. Brown, Gavin P. Wagner

“…In the McMurdo Dry Valleys (MDVs), three decades of high-resolution meteorological monitoring offer a rare opportunity to characterize climate baselines and detect anomalous conditions that may signal extreme events capable of triggering hydrological and ecological responses. …”
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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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Are your kidneys ok? Detect early to protect kidney health by Joseph A. Vassalotti, Anna Francis, Augusto Cesar Soares Dos Santos Jr, Ricardo Correa-Rotter, Dina Abdellatif, Li-Li Hsiao, Stefanos Roumeliotis, Agnes Haris, Latha A. Kumaraswami, Siu-Fai Lui, Alessandro Balducci, Vassilios Liakopoulos

“…using serum creatinine to estimate kidney function and urine albumin to assess for kidney and endothelial damage. …”
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Lightweight Detection Algorithm for Breast-Mass Features in Ultrasound Images by Taojuan Li, Wen Liu, Mingxian Song, Zheng Gu, Ling Hai

“…Thus, the proposed model effectively balances detection performance and lightweight design, making it well-suited for real-time applications on resource-constrained computing devices.…”
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A lightweight personnel detection method for underground coal mines by Shuai WANG, Wei YANG, Yuxiang LI, Jiaqi WU, Wei YANG

“…Introduce SIoU instead of the original loss function to accelerate model convergence. Finally, the introduction of the Ghost module to optimize the backbone network can reduce the computational and parametric quantities of the model without losing the model performance, improve the detection speed, and make the model easier to be deployed on resource-constrained devices. …”
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Are Your Kidneys Ok? Detect Early to Protect Kidney Health by Joseph A. Vassalotti, Anna Francis, Augusto Cesar Soares dos Santos, Jr., Ricardo Correa-Rotter, Dina Abdellatif, Li-Li Hsiao, Stefanos Roumeliotis, Agnes Haris, Latha A. Kumaraswami, Siu-Fai Lui, Alessandro Balducci, Vassilios Liakopoulos

“…using serum creatinine to estimate kidney function and urine albumin to assess for kidney and endothelial damage. …”
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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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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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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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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 application of digital twin technology allows the focus of development to be shifted to the earliest stages, thereby significantly reducing not only potential risks, but also saving the required time and material resources. Classical statistical approaches to evaluating the detection capabilities of radar systems fail to provide a complete dynamic picture due to the large number of varying parameters.Aim. …”
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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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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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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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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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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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