Nguyen The Long

Nguyen The Long
Irkutsk State Technical University · Institute of Information Technology and Data Science

PhD

About

13
Publications
5,309
Reads
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70
Citations
Introduction
Long was born in Thai Nguyen, Vietnam. In 2007, he received a scholarship to Irkutsk National Research Technical University (INRTU), Irkutsk, Russia then graduated here in 2013. Long received his Ph.D. degree in Computer Science in 2017. His present position is Senior Researcher at AI Lab and Lecturer at Baikal School of BRICS, INRTU. His research interests focus on computer vision, image processing, and machine learning. His team won the first prize in the category of "young inventor" in the contest of creative-science projects at science festival INRTU 2018 with project “Road defects detection and classification". His teaching experience: Computer Science, Information Technology (IT) Management at Baikal School of BRICS, Irkutsk National Research Technical University.
Additional affiliations
February 2019 - present
Irkutsk State Technical University
Position
  • Teacher
Description
  • His teaching experience: Computer Science, Information Technology (IT) Management at Baikal School of BRICS
September 2016 - present
Irkutsk State Technical University
Position
  • Researcher
Description
  • Long received his PhD degree in Computer Science from ISTU in 2017. His present position is Researcher at Department of Information Technology, ISTU. His research interests focus on computer vision, images processing and machine learning.

Publications

Publications (13)
Article
Pavement defect detection and classification systems based on machine learning algorithms are already very advanced and are increasingly demonstrating their outstanding advantages. One of the most important steps in the processing is image segmentation. In this paper, some image segmentation algorithms used in practice are presented, compared and e...
Article
Forest fires are one of the causes of significant damage to the ecosystem and serious environmental pollution. Every year, fires in the taiga forest on Russian territory are becoming more serious and complex, which leads to the urgent need to use modern technologies to prevent forest fires. We propose to use modern technologies of artificial intell...
Article
Many methods are proposed in the classification of pavement defects through the extraction of features from data and the use of machine learning algorithms to solve the problem. But there are still limitations such as training time, accuracy and the sensitivity of the system to environmental conditions. This research proposes the method of optimizi...
Article
The fingerprint identification technology has been developed and applied effectively to security systems in financial transactions, personal information security, national security, and other fields. In this paper, we proposed the development of a fingerprint identification system based on image processing methods that clarify fingerprint contours,...
Article
Bubble detection is a challenging problem in automatic process control in the power and energy industry, medical and pharmaceutical industry and many other fields. Computer vision methods applications for bubble detection and measurement is the principal step of robust bubbles monitoring systems development. In various applications the input image...
Article
Full-text available
The system that automatically identifies the anthropometric fingerprint is one of the systems that interact directly with the user, which every day will be provided with a diverse database. This requires the system to be optimized to handle the process to meet the needs of users such as fast processing time, almost absolute accuracy, no errors in t...
Article
Full-text available
ROC analysis is a visual and numerical method used to evaluate the performance of classification algorithms, such as those used to predict the structure and functions from string data. The main objective of the paper is to use the ROC analysis to evaluate the accuracy of the Random Forest algorithm to classify road surface defects on three differen...
Article
Bubbles detection is important in various applications in areas including medicine, process control, geochemistry. The application of computer vision methods enables robust bubbles detection and classification even in complex image registration environments. Complex image background is one of the key issues we studied. Proposed method uses image se...
Article
The novel approach for automatic detection and classification of road defects is proposed based on shape and texture features analysis. The system includes three main steps: defects position detection, feature contour extraction followed by classification of defects. The proposed approach is implemented in Matlab for automatic detection and classif...
Article
The objective of this paper is to propose a robust approach to building a computer vision system to detect and classify pavement defects based on features, such as the contour of feature (chain code histogram, Hu-moment), the shape of an object (length, width, area). In this paper, we present a method to build an automated system to detect and clas...
Article
Full-text available
The contactless automatic anthropometric system is proposed for the reconstruction of the 3D-model of the human body using the conventional smartphone. Our approach involves three main steps. The first step is the extraction of 12 anthropological features. Then we determine the most important features. Finally, we employ these features to build the...
Conference Paper
Full-text available
In this article we propose the novel approach to measure anthropometrical features such as height, width of shoulder, circumference of the chest, hip and waist. The sub-pixel processing and convex hull technique are used to efficiently measure the features from 2d image. The SVM technique is used to classify men and women based on measured features...

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