Youn-Suk Song

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In the field of the service robots, object detection and scene understanding are very important. Conventional methods for object detection are performed with the geometric models, but they have limitations to be used in the uncertain and dynamic environments. This paper proposes a method to predict the probability of target object with Bayesian networks(More)
—As the usage of service robots becomes more sophisticated, direct communication by means of human language is required to increase the efficiency of their performance. In natural speech interaction, however, people often omit some words and rely on background knowledge or the context, resulting in ambiguity. In order to develop smarter service robots,(More)
The service robot supports people in their daily activities, while the interaction between humans and robots seems to be an important part of its performance. Dialogue may be beneficial to the robot to increase the flexibility and facility of the interaction. Traditional robots have merely dealt with simple queries like commands, but in conversation people(More)
It is difficult to understand a scene from visual information in uncertain real world. Since Bayesian network (BN) is known as good in this uncertainty , it has received significant attention in the area of vision-based scene understanding. However, BN-based modeling methods still have the difficulties in modeling complex relationships and combining several(More)
This paper deals with the applications of Artificial Intelligence systems to fault detection in transmission lines. The proposed systems involves Neural Net (NN), Fuzzy Neural (FNN) and Fuzzy Neural Petri Net (FNPN) to implement relays for protection of TL. MATLAB toolbox has been used for simulations and generation of fault data to training and test the(More)
Object detection is very important to service robots. Many tasks for service such as delivery, cleaning, and health-care for elderly people are strongly related to objects. Conventional approaches for object detection are mainly based on the geometric models, because they have been applied to static environments. In indoor environments having uncertainty,(More)
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