Damage Detection in Plates with the Use of Laser-Measured Mode Shapes by Ziemowit Dworakowski, Kajetan Dziedziech, Pawel Zdziebko, Krzysztof Mendrok

“…This paper presents the use of laser vibrometer measurements to detect and locate damage in a metal plate. An algorithm based on local spatial filters was selected, and for the purpose of comparison, the fault location was also determined based on the wavelet analysis of mode shapes. …”
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Application of Artificial Neural Networks for Defect Detection in Ceramic Materials by Tahir Cetin AKINCI, H. Selcuk NOGAY, Ozgur YILMAZ

“…This ANN model was developed to detect whether the plates under test are cracked or not, when four plates have been selected randomly from among a total of 18 ones. …”
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Object detection and tracking in video sequences: formalization, metrics and results by R. P. Bohush, S. V. Ablameyko

“…Based on the considered generalization, an algorithm for tracking people has been developed that uses the tracking through detection method and convolutional neural networks to detect people and form features. …”
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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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Utilizing Calibration Model for Water Distribution Network Leakage Detection by Geumchae Shin, Soon Ho Kwon, Suhyun Lim, Seungyub Lee

“…The proposed model comprises two distinct algorithms: (1) PRC estimation using MCMC and (2) a leakage detection algorithm employing a Kolmogorov–Smirnov test. …”
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Adversarial training driven malicious code detection enhancement method by Yanhua LIU, Jiaqi LI, Zhengui OU, Xiaoling GAO, Ximeng LIU, Weizhi MENG, Baoxu LIU

“…To solve the deficiency of the malicious code detector’s ability to detect adversarial input, an adversarial training driven malicious code detection enhancement method was proposed.Firstly, the applications were preprocessed by a decompiler tool to extract API call features and map them into binary feature vectors.Secondly, the Wasserstein generative adversarial network was introduced to build a benign sample library to provide a richer combination of perturbations for malicious sample evasion detectors.Then, a perturbation reduction algorithm based on logarithmic backtracking was proposed.The benign samples were added to the malicious code in the form of perturbations, and the added benign perturbations were culled dichotomously to reduce the number of perturbations with fewer queries.Finally, the adversarial malicious code samples were marked as malicious and the detector was retrained to improve its accuracy and robustness of the detector.The experimental results show that the generated malicious code adversarial samples can evade the detector well.Additionally, the adversarial training increases the target detector’s accuracy and robustness.…”
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Farsi License Plate Detection and Recognition Based on Characters Features by Sedigheh Ghofrani, Mehran Rasouli

“…In this paper a license plate detection and recognition system for Iranian private cars is implemented. …”
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XGBoost-Based Detection of DDoS Attacks in Named Data Networking by Liang Liu, Weiqing Yu, Zhijun Wu, Silin Peng

“…Through experiments, the performance of the new attacks and the efficacy of the detection algorithm are analyzed. In comparison with other algorithms, the proposed method is demonstrated to have advantages in terms of the advanced nature of the proposed classifier, which is confirmed by the AUC-score.…”
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Saliency Detection via Fusing Color Contrast and Hash Fingerprint by Yin Lv, Xuanrui Zhang, Yong Wang

“…Saliency detection is a technique for automatically extracting regions of interest from the background and has been widely used in the computer vision field. …”
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Robust Symbol Detection in Large-Scale Overloaded NOMA Systems by Hiroki Iimori, Giuseppe Thadeu Freitas De Abreu, Takanori Hara, Koji Ishibashi, Razvan-Andrei Stoica, David Gonzalez G., Osvaldo Gonsa

“…It is also shown via simulations that the technique can be integrated with existing iterative detection-and-decoding (IDD) methods, resulting in accelerated convergence.…”
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Energy optimization using adaptive control algorithm to enhance the performance of SDN_IOT environment by I. Varalakshmi, M. Thenmozhi

“…This paper presents an algorithm for detecting DDoS attacks earlier from the network using the entropy method and mitigating the attacks earlier using stochastic techniques. …”
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Wavelet neural network algorithm for hybrid GA in infrared CO2 gas sensor by Jun Wang, Yuanxi Wang

“…Especially at an ambient temperature of 49 °C, for a true CO2 concentration of 2000 ppm, the detection value processed by the GA-WNN algorithm was 2046 ppm, with a relative error of only 2.3 %, far lower than the 9.8 % of Faster RCNN algorithm and 11.5 % of WNN algorithm. …”
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Accurate detection of selective forwarding attack in wireless sensor networks by Qiong Zhang, Wenzheng Zhang

“…Moreover, to prevent collaborative selective forwarding attack, E-watchdog uses reports from more than one detection agents. Fake reports from attackers are filtered out through an election algorithm. …”
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An attack detection method based on deep learning for internet of things by Yihan Yu, Yu Fu, Taotao Liu, Kun Wang, Yishuai An

“…Additionally, feature redundancy and class imbalance in IoT traffic datasets also constrain detection performance. To address these issues, this paper proposes an attack detection method based on deep learning for IoT. …”
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Comparative Study of Machine Learning Techniques for Insurance Fraud Detection by Navin Duwadi, Anita Sharma

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ECG Paper Digitization and R Peaks Detection Using FFT by Ibraheam Fathail, Vaishali D. Bhagile

“…One of the most essential tools for detecting heart problems is the electrocardiogram (ECG). …”
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Ambulance Siren Detection using Artificial Intelligence in Urban Scenarios by Muhammad Usaid, Muhammad Asif, Tabarka Rajab, Munaf Rashid, Syeda Iqra Hassan

“…With this validated algorithm, researchers can develop a real-time hardware-based model to detect emergency vehicles and make them arrive at the hospital as soon as possible. …”
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An automated platform to detect, assess, and quantify deterioration in concrete structures by Ibrahim Odeh, Behrouz Shafei

“…This study was motivated by the critical need for accurate and fast damage detection in concrete structures, benefiting from significant advantages offered by automated condition assessment strategies compared to manual ones. …”
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Development of an Automatic System to Detect and Spray Herbicides in Corn Fields by Mustafa Üçgül, Hayrettin Karadöl, Ali Aybek

“…In this study, a patch spraying system was developed to automatically detect and spray herbicides on weeds in the corn field based on weed density. …”
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Rice Plant Disease Detection using Convolutional Neural Networks by A. Bala Ayyappan, T. Gobinath, M. Kumar, A. Sivaramakrishnan

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