Tensor RT optimized driver drowsiness detection system using edge device by Chandramohan Dhasarathan, Sambasivam Gnanasekaran, Arnab Pattanayak, Gourav Kumar, Kartik Vig, Vaibhav Narain, K.M. Deva Narayan, Sunidhi Garg

“…The system uses transfer learning techniques for implementing CNN model algorithms to analyze live video from the camera module, allowing for real-time detection of driver behavior such as fatigue or distraction. …”
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A Synergy Between Machine Learning and Formal Concept Analysis for Crowd Detection by Anas M. Al-Oraiqat, Oleksandr Drieiev, Sattam Almatarneh, Mohammadnoor Injadat, Karim A. Al-Oraiqat, Hanna Drieieva, Yassin M. Y. Hasan

“…To enhance public safety, crowd detection and prevention systems have essentially become a natural means to manage diverse crowded areas, such as urban settings, transportation hubs, and event venues. …”
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A Study of Real-time Detection Methods for Solar Radio Burst Identification by YongLin Yu, ChengLong Qiao, Shuo Xu, QinZheng Li, YanRui Su, HongQiang Song, FaBao Yan

“…Spectrum analysis conducted manually or with traditional image processing algorithms is limited by low efficiency and accuracy. …”
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Evaluating the Performance and Potential Bias of Predictive Models for Detection of Transthyretin Cardiac Amyloidosis by Jonathan Hourmozdi, MD, MSAI, MA, Nicholas Easton, MSAI, Simon Benigeri, MSAI, James D. Thomas, MD, Akhil Narang, MD, David Ouyang, MD, Grant Duffy, BS, Ross Upton, PhD, Will Hawkes, PhD, Ashley Akerman, PhD, Ike Okwuosa, MD, Adrienne Kline, MD, PhD, Abel N. Kho, MD, Yuan Luo, PhD, Sanjiv J. Shah, MD, Faraz S. Ahmad, MD, MS

“…Objectives: The aim of this study was to compare the performance of 4 algorithms for ATTR-CM detection in a heart failure population and assess the risk for harms due to model bias. …”
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Transfer learning nonlinear plasma dynamic transitions in low dimensional embeddings via deep neural networks by Zhe Bai, Xishuo Wei, William Tang, Leonid Oliker, Zhihong Lin, Samuel Williams

“…Deep learning algorithms provide a new paradigm to study high-dimensional dynamical behaviors, such as those in fusion plasma systems. …”
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Analysis of Interference Magnetic Field Characteristics of Underwater Gliders by Taotao Xie, Dawei Xiao, Jiawei Zhang, Qing Ji

“…To meet the objective of equipping underwater gliders with magnetic field sensors for underwater target detection, this paper proposes an adaptive filtering method based on the Recursive Least Squares (RLS) algorithm. …”
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Real-time monitoring of water quality dynamics using low-cost sensor networks in Lagos lagoon by Idowu Ayisat Aneyo, Mumin Olatunji Oladipo, Funmilayo Victoria Doherty, Julius Osato Ehigie, Adebayo Fasasi Adebari, Abdulwakeel Oluwatobi Atoyebi, Peter Ozomata Balogun, Ambrose Obinna Ikpele

“…Future research should focus on enhancing wireless communication, refining species detection algorithms and improving sensor resilience in harsh aquatic conditions.…”
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Eye Movement Tracking Using Opencv Python by mohammed satar, Basim Alshammari, Hayder Jasim

“… In this study, we made a simple, low-cost algorithm for tracking eye movements and eye blinks in real-time and non-real-time. …”
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Fast blind detection of short-wave frequency hopping signal based on MeanShift by Zhengyu ZHU, Yu LIN, Zixuan WANG, Kexian GONG, Pengfei CHEN, Zhongyong WANG, Jing LIANG

“…In the complex short-wave channel environment, combined with time-frequency analysis technology, a fast blind detection algorithm of the connected domain labeled frequency hopping signals based on MeanShift algorithm was proposed to reduce the influence of various interference signals and noises on frequency hopping signals and realize blind detection of frequency hopping signals under low signal-to-noise ratio.Firstly, the channel environment gray-scale time-frequency map was filtered by the secondary gray-scale morphology to obtain the binary time-frequency map.Secondly, the maximum duration of the signal was calculated by the connected domain labeling algorithm.Then, the MeanShift algorithm was used to cluster the maximum duration of the signal.Finally, the clustering result was made a second judgment by combining with the adaptive double threshold.The simulation results show that the proposed algorithm can quickly separate various interference signals and sharp noise under low signal-to-noise ratio, and realize fast blind detection of frequency hopping signals without any prior information.It has high detection probability, strong anti-interference ability in short-wave channel environment, low computational complexity and high engineering practical value.…”
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Deep learning algorithm for the automatic assessment of axial vertebral rotation in patients with scoliosis using the Nash–Moe method by Jeoung Kun Kim, Ming Xing Wang, Donghwi Park, Min Cheol Chang

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A two level multi-antenna blind spectrum detection about spatial spectrum by Zhiqiang BAO, Yanrui CUI, Xiao XU

“…In order to improve the perceptual performance,the array spatial spectrum search technology was applied to the spectrum sensing field.A blind spectrum detection algorithm based on two stage detection of spatial spectral values was proposed.Firstly,the maximum and minimum values of the spatial spectrum were used as the test statistics to detect the spectrum.Then the mean value of spatial spectrum for the undetected part was used in the second level detection.By using the advantage of the spatial matching filter,the new algorithm achieved higher detection probability under the low SNR and low sampling rate,and the threshold of detection was accurately deduced based on probability theory.The simulation and comparison results show that TDSS algorithm has better detection effects than some existing classical blind spectrum sensing algorithms.…”
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An Association Rule Mining Scheme Based on Bit Operation and Reverse Index by Yulei Huang, Xiaoxia Luo, Qing Lin

“…An improved Apriori algorithm for association rule mining called Apriori-BR was proposed,which was based on bit operation and reverse index.Specifically,the reverse index from frequent itemsets to transactions was constructed firstly by scanning twice of database,and the reverse index was grouped by the length of transactions.Then in the mining process,bit operation was adopted to accelerate subset detection together with the dynamical elimination of invalid low-dimensional transactions.The numerical results show that the Apriori-BR proposed can substantially improve mining efficiency when compared with the conventional Apriori algorithm and the improved ones in the literature.…”
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Evaluation of Global-Scale and Local-Scale Optimized Segmentation Algorithms in GEOBIA With SAM on Land Use and Land Cover by Tao He, Jianyu Chen, Linchong Kang, Qiankun Zhu

“…However, obtaining outstanding segmentation results in all scenarios proves challenging with a single algorithm. This study investigates seven segmentation algorithms: mean shift (MF), O Sistema de Processamento de informações georreferenciadas (the geographic information and image processing system) (SPRING), Estimation of scale parameter 2 (ESP2) (three global-scale algorithms), image object detection approach (IODA), SA, edge-guided image object detection approach (EIODA) (three local-scale optimization algorithms), and segment anything model (SAM) (deep learning). …”
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Real-time crop row detection using computer vision- application in agricultural robots by Md. Nazmuzzaman Khan, Adibuzzaman Rahi, Veera P. Rajendran, Mohammad Al Hasan, Sohel Anwar

“…The processing of the detection algorithm also must be significantly low for real-time applications. …”
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Artificial Intelligence and Internet of Things-Based Leak Detection Method for the Water Supply Network by Lianxiu Li, Huifan Chen

“…First of all, low-power, low-cost terminal detection equipment and gateway monitoring equipment are developed for remote data transmission through WiFi or cellular data networks. …”
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Tennis automatic ball-picking robot based on image object detection and positioning technology by Huang Yaqiao, Xiang Yu

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Research on Early Diagnosis Methods for Broiler Chicken Diseases Based on Swarm Intelligence Optimization Algorithms and Random Forest by X Peng, C Chen, L Yu, X Kong, B Sun

“…This study introduces a novel methodology for broiler disease diagnosis and prediction, substantially improving accuracy and efficiency while maintaining low computational costs. The proposed framework can be seamlessly integrated into IoT-based broiler health monitoring platforms, offering valuable theoretical foundations and technical support for disease detection and prevention in poultry farming.…”
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Improved OAM-Based Radar Targets Detection Using Uniform Concentric Circular Arrays by Mingtuan Lin, Yue Gao, Peiguo Liu, Jibin Liu

“…However, the main estimation method, that is, Fast Fourier Transform (FFT), under this scheme suffers from low resolution. As a solution, this paper rebuilds the OAM-based radar targets detection model and introduces the multiple signal classification (MUSIC) algorithm to improve the resolution for detecting targets within the main lobes. …”
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Automatic detection and tracking the moving objects observed by an unmanned aerial vehicles video camera by R. S. Zhuk

“…The indication of objects as moving occurs only if during the time of its tracking it has shifted a considerable distance. The algorithm has a low percentage of false detections of moving objects, it detects well small objects and is capable reliably to accompany moving objects.…”
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Accurate Indoor Localization with IoT Devices and Advanced Fingerprinting Methods by Farshad Khodamoradi, Javad Rezazadeh, John Ayoade

“…The study evaluates the effectiveness of iBeacon transmitters for indoor positioning, comparing the Weighted Centroid Localization (WCL) and Positive Weighted Centroid Localization (PWCL) algorithms, along with fingerprinting methods enhanced by outlier detection and mapping filters. …”
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