Enhanced Curvature-Based Fabric Defect Detection: A Experimental Study with Gabor Transform and Deep Learning by Mehmet Erdogan, Mustafa Dogan

“…The primary contribution of this work is the development of a modified curvature algorithm that achieves high classification performance without the need for training. …”
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Detecting SARS-CoV-2 in CT Scans Using Vision Transformer and Graph Neural Network by Kamorudeen Amuda, Almustapha Wakili, Tomilade Amoo, Lukman Agbetu, Qianlong Wang, Jinjuan Feng

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Towards Effective Parkinson’s Monitoring: Movement Disorder Detection and Symptom Identification Using Wearable Inertial Sensors by Umar Khan, Qaiser Riaz, Mehdi Hussain, Muhammad Zeeshan, Björn Krüger

“…The proposed pipeline employs and evaluates manual feature crafting for classical machine learning algorithms, as well as an RNN-CNN-inspired deep learning model that does not require manual feature crafting. …”
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DGSS-YOLOv8s: A Real-Time Model for Small and Complex Object Detection in Autonomous Vehicles by Siqiang Cheng, Lingshan Chen, Kun Yang

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DETECTION OF DIRECT CONTROL LINES ON AEROVIEWS BASE ON EKKLIDOV FORM FACTOR by O. G. Shevchuk, V. Yu. Tsviatkou

“…The algorithm of detection of direct contour lines base on euclidean form factor is presented. …”
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An Efficient Collision Detection Method for Computing Discrete Logarithms with Pollard's Rho by Ping Wang, Fangguo Zhang

“…In this paper, we present a new efficient collision detection algorithm for Pollard's rho method. The new algorithm is more efficient than the previous distinguished point method and can be easily adapted to other applications. …”
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Validating a smart bed against polysomnography for sleep apnea detection by Farzad Siyahjani, Kostiantyn Kalenyk, Gary Garcia-Molina, Saeed Babaeizadeh

“…The algorithm aims to detect SDB events and estimate whether the apnea-hypopnea index (AHI) is ≥ 15, indicative of moderate to severe apnea. …”
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gfpop: An R Package for Univariate Graph-Constrained Change-Point Detection by Vincent Runge, Toby Dylan Hocking, Gaetano Romano, Fatemeh Afghah, Paul Fearnhead, Guillem Rigaill

“… In a world with data that change rapidly and abruptly, it is important to detect those changes accurately. In this paper we describe an R package implementing a generalized version of an algorithm recently proposed by Hocking, Rigaill, Fearnhead, and Bourque (2020) for penalized maximum likelihood inference of constrained multiple change-point models. …”
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Fault detection and diagnosis method for heterogeneous wireless network based on GAN by Xiaorong ZHU, Peipei ZHANG

“…Aiming at the problem that in the process of network fault detection and diagnosis,how to train the precise fault diagnosis and detection model based on small data volume,a fault diagnosis and detection algorithm based on generative adversarial networks (GAN) for heterogeneous wireless networks was proposed.Firstly,the common network fault sources in heterogeneous wireless network environment was analyzed,and a large number of reliable data sets was obtained based on a small amount of network fault samples through GAN algorithm.Then,the extreme gradient boosting (XGBoost) algorithm was used to select the optimal feature combination of input parameters in the fault detection stage and completed fault diagnosis and detection based on these data.Simulation results show that the algorithm can achieve more accurate and efficient fault detection and diagnosis for heterogeneous wireless networks,with an accuracy of 98.18%.…”
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Fault detection and diagnosis method for heterogeneous wireless network based on GAN by Xiaorong ZHU, Peipei ZHANG

“…Aiming at the problem that in the process of network fault detection and diagnosis,how to train the precise fault diagnosis and detection model based on small data volume,a fault diagnosis and detection algorithm based on generative adversarial networks (GAN) for heterogeneous wireless networks was proposed.Firstly,the common network fault sources in heterogeneous wireless network environment was analyzed,and a large number of reliable data sets was obtained based on a small amount of network fault samples through GAN algorithm.Then,the extreme gradient boosting (XGBoost) algorithm was used to select the optimal feature combination of input parameters in the fault detection stage and completed fault diagnosis and detection based on these data.Simulation results show that the algorithm can achieve more accurate and efficient fault detection and diagnosis for heterogeneous wireless networks,with an accuracy of 98.18%.…”
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A Method for Community Detection of Complex Networks Based on Hierarchical Clustering by Chuantao Yin, Shuaibing Zhu, Hui Chen, Bingxue Zhang, Bertrand David

“…This paper proposes an algorithm for community detection based on hierarchical clustering (CDHC Algorithm). …”
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Statistically Bounding Detection Latency in Low-Duty-Cycled Sensor Networks by Yanmin Zhu

“…In addition, the algorithm exposes a convenient interface for users to define the requirement on detection latency, thereby tuning the intrinsic tradeoff between energy efficiency and event detection performance. …”
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TSHD: Topic Segmentation Based on Headings Detection (Case Study: Resumes) by Majd E. Tannous, Wassim H. Ramadan, Mohanad A. Rajab

“…This research presents a new algorithm named TSHD for topic segmentation based on headings detection. …”
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Detection of multiple pesticide residues on the surface of broccoli based on hyperspectral imaging by GUI Jiangsheng, GU Min, WU Zixian, BAO Xiao’an

“…A method for the detection of pesticide residues on broccoli was proposed based on hyperspectral image technology. …”
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Multiresolution Rotational Symmetry Detection via Radius-Based Frieze-Expansion by Gang Pan, Di Sun, Yarui Chen, Chuanlei Zhang

“…However, it remains difficult to design an effective algorithm for automatic symmetry recognition. In this paper, we present a rotational symmetry detection algorithm, which is easy to use and can determine both the center and the radius of the rotational symmetry supporting region without human interaction. …”
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Comparative Analysis of Anomaly Detection Techniques Using Generative Adversarial Network by Imran Ullah Khan, Shah Noor, Ahthasham Sajid, Junaid Javaid, Iqra Tabasusum

“…However, it is difficult to choose one anomaly detection algorithm over another because each algorithm stands out with its own performance. …”
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Background dictionary construction-based sparse representation hyperspectral target detection by Tao Yang, Lin Feipeng, Yang Wen, Weng Shan

“…A sparse representation hyperspectral target detection algorithm based on background dictionary is proposed. …”
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Detect Flame Fire Using Fractal Geometry in Color Digital Images by Laheeb Ibrahim, Khalil Alsaif, Hasan Alnima

“…In this research an algorithm for detecting fire flame in the colored digital images is built. …”
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Comparison of Support Vector Machine-Based Techniques for Detection of Bearing Faults by Lijun Wang, Shengfei Ji, Nanyang Ji

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Robust cooperative spectrum sensing in cognitive radio blockchain network using SHA-3 algorithm by Evelyn Ezhilarasi I, J. Christopher Clement

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