• Journal of IKEEE
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• v.22 no.4
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• pp.1079-1087
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• 2018

Recently, computer vision field based deep learning artificial intelligence has become a hot topic among various image analysis boundaries. In this study, flames are detected in fire images using the Faster R-CNN algorithm, which is used to detect objects within the image, among various image recognition algorithms based on deep learning. In order to improve fire detection accuracy through a small amount of data sets in the learning process, we use image augmentation techniques, and learn image augmentation by dividing into 6 types and compare accuracy, precision and detection rate. As a result, the detection rate increases as the type of image augmentation increases. However, as with the general accuracy and detection rate of other object detection models, the false detection rate is also increased from 10% to 30%.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.1
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• pp.99-104
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• 2022

Artificial intelligence is getting a crucial part of our lives with its incredible benefits. Machines outperform humans in recognizing objects in images, particularly in classifying people into correct age and gender groups. In this respect, age and gender classification has been one of the hot topics among computer vision researchers in recent decades. Deployment of deep Convolutional Neural Network(: CNN) models achieved state-of-the-art performance. However, the most of CNN based architectures are very complex with several dozens of training parameters so they require much computation time and resources. For this reason, we propose a new CNN-based classification algorithm with significantly fewer training parameters and training time compared to the existing methods. Despite its less complexity, our model shows better accuracy of age and gender classification on the UTKFace dataset.

• Journal of the Korea Computer Graphics Society
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• v.30 no.2
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• pp.11-19
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• 2024

Demand for small biomimetic robots that can carry out reconnaissance missions without being exposed to the enemy in underground spaces and narrow passages is increasing in order to increase the fighting power and survivability of soldiers in wartime situations. A small compound eye image sensor for environmental recognition has advantages such as small size, low aberration, wide angle of view, depth estimation, and HDR that can be used in various ways in the field of vision. However, due to the small lens size, the resolution is low, and the problem of resolution in the fused image obtained from the actual compound eye image occurs. This paper proposes a compound eye image quality enhancement algorithm based on Image Enhancement and ESRGAN to overcome the problem of low resolution. If the proposed algorithm is applied to compound eye image fusion images, image resolution and image quality can be improved, so it is expected that performance improvement results can be obtained in various studies using compound eye cameras.

• The Journal of Bigdata
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• v.9 no.1
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• pp.89-100
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• 2024

In the field of computer vision, models such as You Look Only Once (YOLO) and ResNet are widely used due to their real-time performance and high accuracy. However, to apply these models in real-world environments, factors such as runtime compatibility, memory usage, computing resources, and real-time conditions must be considered. This study compares the characteristics of three deep model runtimes: ONNX Runtime, TensorRT, and OpenCV DNN, and analyzes their performance on two models. The aim of this paper is to provide criteria for runtime selection for practical applications. The experiments compare runtimes based on the evaluation metrics of time, memory usage, and accuracy for vehicle license plate recognition and classification tasks. The experimental results show that ONNX Runtime excels in complex object detection performance, OpenCV DNN is suitable for environments with limited memory, and TensorRT offers superior execution speed for complex models.

• Journal of Legislation Research
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• no.53
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• pp.553-591
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• 2017

This article discussed whether so-called 'foreign judgments obtained by fraud' is in breach of public policy provided in Article 217(1)(3) of Civil Procedure Act and, if so, what the specific requirements could be. The summary of the conclusion is as follows. The 'foreign judgments obtained by fraud' is against the municipal procedural public policy and then shall not be recognized. In this regard one more question comes up whether reviewing if 'foreign judgments obtained by fraud' is in breach of the municipal procedural public policy is allowed in consideration of the principle of prohibition of $r{\acute{e}}vision$ au fond. Since the principle is applied entirely in the course of the above reviewing, it is allowed only when it does not breach the principle. The two instances that the reviewing is allowed are where the defendant was not able to produce evidences of fraud during foreign procedures and where the defendant's claim of fraud without evidences was rejected by the foreign court and then evidences of fraud were found after the foreign procedure was completed. On the other hand, the specific requirements for 'foreign judgments obtained by fraud' to be against public policy are following four requirements based on principle of strict interpretation of public policy. (1) plaintiff's intention to fraud, (2) preventing the defendant from being involved in the procedure by fraud or cheating the foreign court using manipulated evidences, (3) the defendant could not present himself in the foreign court procedure due to the plaintiff's extraneous fraud or the foreign court decided wrongly due to intrinsic fraud, and (4) defendant's fundamental procedural rights were breached to the extent that recognizing the effect of foreign judgments was against justice defendant's fundamental procedural rights. These results differ from the Supreme Court 2004. 10. 28. ruling 2002da74213 in many aspects. Most of all, in my opinion there is no need to distinguish between intrinsic fraud and extraneous fraud and reviewing 'foreign judgments obtained by fraud' is not in conflict with the principle of prohibition of $r{\acute{e}}vision$ au fond but the both may coexist. In this regard I expect the variation of the Supreme Court's position and hope to contribute to academia and practitioners.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.1-19
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• 2019

Artificial intelligence (AI) is one of the main driving forces leading the Fourth Industrial Revolution. The technologies associated with AI have already shown superior abilities that are equal to or better than people in many fields including image and speech recognition. Particularly, many efforts have been actively given to identify the current technology trends and analyze development directions of it, because AI technologies can be utilized in a wide range of fields including medical, financial, manufacturing, service, and education fields. Major platforms that can develop complex AI algorithms for learning, reasoning, and recognition have been open to the public as open source projects. As a result, technologies and services that utilize them have increased rapidly. It has been confirmed as one of the major reasons for the fast development of AI technologies. Additionally, the spread of the technology is greatly in debt to open source software, developed by major global companies, supporting natural language recognition, speech recognition, and image recognition. Therefore, this study aimed to identify the practical trend of AI technology development by analyzing OSS projects associated with AI, which have been developed by the online collaboration of many parties. This study searched and collected a list of major projects related to AI, which were generated from 2000 to July 2018 on Github. This study confirmed the development trends of major technologies in detail by applying text mining technique targeting topic information, which indicates the characteristics of the collected projects and technical fields. The results of the analysis showed that the number of software development projects by year was less than 100 projects per year until 2013. However, it increased to 229 projects in 2014 and 597 projects in 2015. Particularly, the number of open source projects related to AI increased rapidly in 2016 (2,559 OSS projects). It was confirmed that the number of projects initiated in 2017 was 14,213, which is almost four-folds of the number of total projects generated from 2009 to 2016 (3,555 projects). The number of projects initiated from Jan to Jul 2018 was 8,737. The development trend of AI-related technologies was evaluated by dividing the study period into three phases. The appearance frequency of topics indicate the technology trends of AI-related OSS projects. The results showed that the natural language processing technology has continued to be at the top in all years. It implied that OSS had been developed continuously. Until 2015, Python, C ++, and Java, programming languages, were listed as the top ten frequently appeared topics. However, after 2016, programming languages other than Python disappeared from the top ten topics. Instead of them, platforms supporting the development of AI algorithms, such as TensorFlow and Keras, are showing high appearance frequency. Additionally, reinforcement learning algorithms and convolutional neural networks, which have been used in various fields, were frequently appeared topics. The results of topic network analysis showed that the most important topics of degree centrality were similar to those of appearance frequency. The main difference was that visualization and medical imaging topics were found at the top of the list, although they were not in the top of the list from 2009 to 2012. The results indicated that OSS was developed in the medical field in order to utilize the AI technology. Moreover, although the computer vision was in the top 10 of the appearance frequency list from 2013 to 2015, they were not in the top 10 of the degree centrality. The topics at the top of the degree centrality list were similar to those at the top of the appearance frequency list. It was found that the ranks of the composite neural network and reinforcement learning were changed slightly. The trend of technology development was examined using the appearance frequency of topics and degree centrality. The results showed that machine learning revealed the highest frequency and the highest degree centrality in all years. Moreover, it is noteworthy that, although the deep learning topic showed a low frequency and a low degree centrality between 2009 and 2012, their ranks abruptly increased between 2013 and 2015. It was confirmed that in recent years both technologies had high appearance frequency and degree centrality. TensorFlow first appeared during the phase of 2013-2015, and the appearance frequency and degree centrality of it soared between 2016 and 2018 to be at the top of the lists after deep learning, python. Computer vision and reinforcement learning did not show an abrupt increase or decrease, and they had relatively low appearance frequency and degree centrality compared with the above-mentioned topics. Based on these analysis results, it is possible to identify the fields in which AI technologies are actively developed. The results of this study can be used as a baseline dataset for more empirical analysis on future technology trends that can be converged.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.1059-1068
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• 2011

This study is aimed to systematically grasp the visual and informative needs of sign system and secure the formativeness sample for standardization model. This study, therefore, will help building the requirements to create design value and secure objectiveness for realization of practical use of the communication design plan, and means transference of the external and internal information system of railroad vehicles for practical use into the standardization model. The pictorial sign based information delivery is a communication process and way gained through vision and perception, so that grasping the formative structure connoted in message is not less than understanding the characteristics of the essence. In this study, I defined the symbolic expressions inherent in TTX sign system to be perceptional action and value norms as general signatures and signifiers.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.6C
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• pp.593-603
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• 2009

In this paper, we propose a new integrated computer vision system designed to track multiple human beings and extract their silhouette with an active stereo camera. The proposed system consists of three modules: detection, tracking and silhouette extraction. Detection was performed by camera ego-motion compensation and disparity segmentation. For tracking, we present an efficient mean shift based tracking method in which the tracking objects are characterized as disparity weighted color histograms. The silhouette was obtained by two-step segmentation. A trimap is estimated in advance and then this was effectively incorporated into the graph cut framework for fine segmentation. The proposed system was evaluated with respect to ground truth data and it was shown to detect and track multiple people very well and also produce high quality silhouettes. The proposed system can assist in gesture and gait recognition in field of Human-Robot Interaction (HRI).

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1591-1596
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• 1991

The present paper describes a method of recognizing a polyhedron employing the notion of network constraint analysis. Typical difficulties in three-dimensional object recognition, other than shading, reflection, and hidden line problems, include the case where appearances of an object vary according to observation points and the case where an object to be recognized is occluded by other objects placed in its front, resulting in incomplete information on the object shape. These difficulties can, however, be solved to a large extent, by taking account of certain local constraints defined on a polyhedral shape. The present paper assumes a model-based vision employing an appearance-oriented model of a polyhedron which is provided by placing it at the origin of a large sphere and observing it from various positions on the surface of the sphere. The model is actually represented by the sets of adjacent faces pairs of the polyhedron observed from those positions. Since the shape of a projected face gives constraint to that of its adjacent face, this results in a local constraint relation between these faces. Each projected face of an unknown polyhedron on an acquired image is examined its match with those faces in the model, producing network constraint relations between faces in the image and faces in the model. Taking adjacency of faces into consideration, these network constraint relations are analyzed. And if the analysis finally provides a solution telling existence of one to one match of the faces between the unknown polyhedron and the model, the unknown polyhedron is understood to be one of those memorized models placed in a certain posture. In the performed experiment, a polyhedron was observed from 320 regularly arranged points on a sphere to provide its appearance model and a polyhedron with arbitrarily postured, occluded, or imposed another difficulty was successfully recognized.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.5
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• pp.13-24
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• 2011

This paper deals with a 3D-pose (orientation and position) estimation problem of a circular object in 3D-space. Circular features can be found with many objects in real world, and provide crucial cues in vision-based object recognition and location. In general, as a circular feature in 3D space is perspectively projected when imaged by a camera, it is difficult to recover fully three-dimensional orientation and position parameters from the projected curve information. This paper therefore proposes a 3D pose estimation method of a circular feature using a coplanar point. We first interpret a circular feature with a coplanar point in both the projective space and 3D space. A procedure for estimating 3D orientation/position parameters is then described. The proposed method is verified by a numerical example, and evaluated by a series of experiments for analyzing accuracy and sensitivity.