LiDAR-Based Detection of Urban Trees Using a Backpack System by M. F. da Silva, L. F. Castanheiro, A. M. G. Tommaselli, A. M. G. Tommaselli, R. C. dos Santos, R. C. dos Santos, M. Galo, M. Galo

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Automated Caries Detection Under Dental Restorations and Braces Using Deep Learning by Yi-Cheng Mao, Yuan-Jin Lin, Jen-Peng Hu, Zi-Yu Liu, Shih-Lun Chen, Chiung-An Chen, Tsung-Yi Chen, Kuo-Chen Li, Liang-Hung Wang, Wei-Chen Tu, Patricia Angela R. Abu

“…This study proposes an innovative deep learning and image processing-based approach for automated caries detection under restoration and dental braces, aiming to reduce the clinical burden on dental practitioners. …”
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Early Fault Detection in FOC Driven Induction Motors: A Case Study by Isabela O. Zaparoli, Arismar M. G. Junior, Marco Tulio A. Evo, Diogo S. C. Souza, Helder de Paula

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Detection of African swine fever virus in pork products brought to Taiwan by travellers by Wen-Hung Wang, Chih-Yen Lin, Max R. Chang Ishcol, Aspiro Nayim Urbina, Wanchai Assavalapsakul, Arunee Thitithanyanont, Po-Liang Lu, Yen-Hsu Chen, Sheng-Fan Wang

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Evaluating Machine Learning Algorithms for Financial Fraud Detection: Insights from Indonesia by Cheng-Wen Lee, Mao-Wen Fu, Chin-Chuan Wang, Muh. Irfandy Azis

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Interpretable Deep Learning for Pneumonia Detection Using Chest X-Ray Images by Jovito Colin, Nico Surantha

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USE OF NEURAL NETWORKS FOR DETECTION AND RECOGNITION OF THE ANOMALIES IN ENTERPRISE CORPORATIVE INFORMATION SYSTEM by U. A. Vishniakou, O. S. Koval, M. G. Mozdurani Shiraz

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Ultra tough and high resilience mechanochromic fibres for real world stress detection by Yu Jin Jeong, Youngeun Lee, Taekyung Won, Ji Won Lee, Youngho Eom, Dae Seok Kim

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Research on industrial control system intrusion detection method based on simulation modelling by Yi-wei GAO, Rui-kang ZHOU, Ying-xu LAI, Ke-feng FAN, Xiang-zhen YAO, Lin LI

“…At present,intrusion detection system over fieldbus network layer was a basic protection method in industrial control system.However,it has some weakness,such as poor generality,high false-positive rate,and unable to detect unknown anomaly.An industrial control system intrusion detection method based on fieldbus network equipment simulation was proposed.The method prevented control program from being tampered or destroyed based on controller simulation modelling.Controlled object simulation modelling was designed for ensuring that the system input was credible.Thus the intrusion detection of industrial control network was realized.At last,the results indicate that the proposed intrusion detecting method is available.…”
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Game-based detection method of broken access control vulnerabilities in Web application by HE Haitao, XU Ke, YANG Shuailin, ZHANG Bing, ZHAO Yuxuan, LI Jiazheng

“…To solve the problem that the access control strategy of the program in the industrial Internet was difficult to extract from the source code, and that the user’s access operation was difficult to trigger all access paths, which led to the difficulty of universal detection of logical vulnerabilities, game theory was applied to the access control logic vulnerability detection for the first time. …”
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MAGECODE: Machine-Generated Code Detection Method Using Large Language Models by Hung Pham, Huyen Ha, van Tong, Dung Hoang, Duc Tran, Tuyen Ngoc Le

“…Consequently, various machine-generated text (MGT) detection methods, developed from metric-based and model-based approaches, were proposed and shown to be highly effective. …”
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Accelerated active case detection of visceral leishmaniasis patients in endemic villages of Bangladesh. by Jahanara Khatun, M Mamun Huda, Md Shakhawat Hossain, Wolfgang Presber, Debashis Ghosh, Axel Kroeger, Greg Matlashewski, Dinesh Mondal

“…We recommend that the National VL Program should consider AACD to strengthen its early VL case detection strategy.…”
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Intelligent vulnerability detection system based on graph structured source code slice by Deqing ZOU, Xiang LI, Minhuan HUANG, Xiang SONG, Hao LI, Weiming LI

“…For the intelligent vulnerability detection, the system extracts the graph structured source code slices according to the vulnerability characteristics from the program dependency graph of source code, and then presents the graph structured slice information to carry out vulnerability detection by using the graph neural network model.Slice level vulnerability detection was realized and the vulnerability line was located at the code line level.In order to verify the effectiveness of the system, compared with the static vulnerability detection systems, the vulnerability detection system based on serialized text information, and the vulnerability detection system based on graph structured information, the experimental results show that the proposed system has a high accuracy in the vulnerability detection capability and a good performance in the vulnerability code line prediction.…”
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Biological markers of auditory gap detection in young, middle-aged, and older adults. by Bernhard Ross, Bruce Schneider, Joel S Snyder, Claude Alain

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Detection of Victimization Patterns and Risk of Gender Violence Through Machine Learning Algorithms by Edna Rocio Bernal-Monroy, Erika Dajanna Castañeda-Monroy, Rafael Ricardo Rentería-Ramos, Sixto Enrique Campaña-Bastidas, Jessica Barrera, Tania Maribel Palacios-Yampuezan, Olga Lucía González Gustin, Carlos Fernando Tobar-Torres, Zeneida Rocio Ceballos-Villada

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Asumu Fractional Derivative Applied to Edge Detection on SARS-COV2 Images by Gustavo Asumu Mboro Nchama, Leandro Daniel Lau Alfonso, Roberto Rodríguez Morales, Ezekiel Nnamere Aneke

“…The experimental comparison show that the proposed method outperforms some edge detection methods. In the next paper, we are planning to improve and combine the proposed filters with artificial intelligence algorithm in order to program a training system for SARS-COV2 image classification with the aim of having a supplemental medical diagnostic.…”
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A non-anatomical graph structure for boundary detection in continuous sign language by Razieh Rastgoo, Kourosh Kiani, Sergio Escalera

“…More concretely, the content of each window is processed using the pre-trained model obtained from the first step and the class probabilities of the Fully Connected (FC) layer embedded in the Transformer model are fed to the post-processing module, which aims to detect the accurate boundary of the un-processed isolated signs. …”
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A simultaneous EEG and eye-tracking dataset for remote sensing object detection by Bing He, Hongqiang Zhang, Tong Qin, Bowen Shi, Qiao Wang, Weihua Dong

“…This task reflects the typical cognitive processes associated with human visual search and object identification in remote sensing imagery. …”
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Development of alternative models for early detection of religiously legitimated anarchism in Bali Province by Ni Nyoman Lisna Handayani

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Single-Frame Infrared Target Detection Based on Fast Content-Related Modeling by Zipeng Zhang, Xidong Zhao, Wenzheng Wang, Yuqi Han, Chenwei Deng, Zhuokai Li, Linbo Tang

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