• Journal of Institute of Control, Robotics and Systems
• /
• v.8 no.7
• /
• pp.589-598
• /
• 2002

The color measuring/matching expert system is implemented with a new color measuring method that combines intelligent algorithms with image processing techniques. Color measuring part of the proposed system preprocesses the scanned original color input images to eliminate their distorted components by means of the image histogram technique of image pixels, and then extracts RGB(Red, Green, Blue)data among color information from preprocessed color input images. If the extracted RGB color data does not exist on the matching recipe databases, we can measure the colors for the user who want to implement the model that can search the rules for the color mixing information, using the intelligent modeling techniques such as fuzzy inference system and adaptive neuro-fuzzy inference system. Color matching part can easily choose images close to the original color for the user by comparing information of preprocessed color real input images with data-based measuring recipe information of the expert, from the viewpoint of the delta Eformula used in practical process.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.13 no.3
• /
• pp.366-370
• /
• 2003

In this research, we suggest a hybrid intelligent Web recommendation systems based on Web data mining and case-based reasoning (CBR). One of the important research topics in the field of Internet business is blending artificial intelligence (AI) techniques with knowledge discovering in database (KDD) or data mining (DM). Data mining is used as an efficient mechanism in reasoning for association knowledge between goods and customers＇ preference. In the field of data mining, the features, called attributes, are often selected primary for mining the association knowledge between related products. Therefore, most of researches, in the arena of Web data mining, used association rules extraction mechanism. However, association rules extraction mechanism has a potential limitation in flexibility of reasoning. If there are some goods, which were not retrieved by association rules-based reasoning, we can＇t present more information to customer. To overcome this limitation case, we combined CBR with Web data mining. CBR is one of the AI techniques and used in problems for which it is difficult to solve with logical (association) rules. A Web-log data gathered in real-world Web shopping mall was given to illustrate the quality of the proposed hybrid recommendation mechanism. This Web shopping mall deals with remote-controlled plastic models such as remote-controlled car, yacht, airplane, and helicopter. The experimental results showed that our hybrid recommendation mechanism could reflect both association knowledge and implicit human knowledge extracted from cases in Web databases.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.168.2-168
• /
• 2001

Generally, operators suffer much difficulty in manipulating micro-nano-sized objects without assisting of human interface, due to the scaling effects in micro/nano world. Thus, the micromanipulation system based on the teleoperation techniques enables operators to manipulate the micro objects easily by transferring both human motion and manipulation skills to the micromanipulator. In teleoperated microassembly, it is necessary to provide a useful user interface for facilitating micro assembly task executed by human operators. In this paper, Intelligent User Interface (UI) for teleoperated microassembly is proposed. The proposed intelligent UI improves task performance by teleoperated micromanipulation as well as guides operators to succeed in desirable ...

• Journal of Institute of Control, Robotics and Systems
• /
• v.20 no.3
• /
• pp.245-260
• /
• 2014

Referring to various definitions, we first examine the identity issue of intelligent control and, have tried to explain the nature and attributes of intelligent control in terms of two categories of positions, that is, the Noumenalist's position and the Phenomenologist's position. And then, we give detailed descriptions for (1) FUZZY-based intelligent control and (2) learning control. Finally, as a noticeable new technique of intelligent control for robotic applications, we present (3) Cognitive control.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.7 no.1
• /
• pp.41-48
• /
• 2007

Latest advances in network sensor technology and state of the art of mobile robot, and artificial intelligence research can be employed to develop autonomous and distributed monitoring systems. In this study, as the preliminary step for developing a multi-purpose "Intelligent Space" platform to implement advanced technologies easily to realize smart services to human. We will give an explanation for the ISpace system architecture designed and implemented in this study and a short review of existing techniques, since there exist several recent thorough books and review paper on this paper. Instead we will focus on the main results with relevance to the DIND data fusion with CI of Intelligent Space. We will conclude by discussing some possible future extensions of ISpace. It is first dealt with the general principle of the navigation and guidance architecture, then the detailed functions tracking multiple objects, human detection and motion assessment, with the results from the simulations run.

• Journal of Intelligence and Information Systems
• /
• v.15 no.4
• /
• pp.99-121
• /
• 2009

Recently, there have been many studies that predict corporate bankruptcy using data mining techniques. Although various data mining techniques have been investigated, some researchers have tried to combine the results of each data mining technique in order to improve classification performance. In this study, we classify 4 types of data mining techniques via their characteristics and select representative techniques of each type then combine them using a genetic algorithm. The genetic algorithm may find optimal or near-optimal solution because it is a global optimization technique. This study compares the results of single models, typical combination models, and the proposed integration model using the genetic algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.11
• /
• pp.5474-5490
• /
• 2017

Although two-dimensional principal component analysis (2DPCA) has been shown to be successful in face recognition system, it is still very sensitive to illumination variations. To reduce the effect of these variations, texture-based techniques are used due to their robustness to these variations. In this paper, we explore several texture-based techniques and determine the most appropriate one to be used with 2DPCA-based techniques for face recognition. We also propose a new distance metric computation in 2DPCA called Row Assembled Matrix Distance (RowAMD). Experiments on Yale Face Database, Extended Yale Face Database B, AR Database and LFW Database reveal that the proposed RowAMD distance computation method outperforms other conventional distance metrics when Local Line Binary Pattern (LLBP) and Multi-scale Block Local Binary Pattern (MB-LBP) are used for face authentication and face identification, respectively. In addition to this, the results also demonstrate the robustness of the proposed RowAMD with several texture-based techniques.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.20 no.6
• /
• pp.313-330
• /
• 2021

In an autonomous driving system equipped with a camera and lidar, depth completion techniques enable dense depth estimation. In particular, using self-supervised learning it is possible to train the depth completion network even without ground truth. In actual autonomous driving, such depth completion should have very short latency as it is the input of other algorithms. So, rather than complicate the network structure to increase the accuracy like previous studies, this paper focuses on network latency. We design a U-Net type network with RegNet encoders optimized for GPU computation. Instead, this paper presents several techniques that can increase accuracy during the process of self-supervised learning. The proposed techniques increase the robustness to unreliable lidar inputs. Also, they improve the depth quality for edge and sky regions based on the semantic information extracted in advance. Our experiments confirm that our model is very lightweight (2.42 ms at 1280x480) but resistant to noise and has qualities close to the latest studies.

• Journal of the Korea Computer Industry Society
• /
• v.7 no.5
• /
• pp.503-512
• /
• 2006

Recently, intelligent agents are demanded increasingly automated techniques for animation according to interaction with user or environment of the user. In this paper, we have studied a generic framework for intelligent agents based on emotions. Intelligent agents are designed to infer emotions from diverse personalities, situations, user behaviors and to express them. We research into the technique and the case study for intelligent agents based on emotions supposing autonomous and interactive animation.

• The Journal of Korea Robotics Society
• /
• v.1 no.1
• /
• pp.36-45
• /
• 2006

In this paper, we introduce visual contexts in terms of types and utilization methods for robust object recognition with intelligent mobile robots. One of the core technologies for intelligent robots is visual object recognition. Robust techniques are strongly required since there are many sources of visual variations such as geometric, photometric, and noise. For such requirements, we define spatial context, hierarchical context, and temporal context. According to object recognition domain, we can select such visual contexts. We also propose a unified framework which can utilize the whole contexts and validates it in real working environment. Finally, we also discuss the future research directions of object recognition technologies for intelligent robots.