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Interactive dynamic influence diagrams (I-DIDs) are graphical models of sequential decision-making in uncertain multi-agent setting. Algorithms for solving I-DIDs face the challenge of an exponentially growing space of candidate models over time. In this paper, we discuss a class of candidate models that are auto orphism POMDPs and present a method of solving candidate models of I-DIDs. We do this...
Clothes products contain many characteristics which are difficult to describe in keywords, such as texture, shape, or the relationship between object and space. Based on this issue, we develop an image-based visual clothing retrieval system, which extracts and uses the features of clothing images to find objects that are difficult to describe by text, or without text annotations. We integrate techniques...
In recent years, the gesture control technique has become a new developmental trend for many human-based electronics products. This technique let people can control these products more naturally, intuitively and conveniently. In this paper, a fast gesture recognition scheme is proposed to be an interface for the human-machine interaction (HMI) of systems. This paper presents some low-complexity algorithms...
This paper explains the development of an algorithm that approximates edge detection on a digital image. The algorithm uses an artificial neural network, trained by our implementation of the error-correction learning algorithm. In this paper, the results using our algorithm are compared to the results of the methods Canny and Sobel which are two of the widest known edge detection algorithms. The proposed...
This paper describes the stock price return prediction algorithms by using Bayesian network. In the first algorithm, the clustering algorithm transforms the stock price return distribution to the discrete values set. The Bayesian network gives the probabilistic graphical model that represents previous stock price returns and their conditional dependencies via a directed a cyclic graph. The network...
This paper analyzes the biometric identification and tracking related technologies of human-computer interaction. Based on Adaboost face detection algorithm, we propose a position-based head motion detection algorithm, which does not depend on the specific biometric identification and tracking. It uses feature classification method to detect mouth's opening and closing actions. We also design a software...
Recently, the number of people who use recipe sites is increasing. Since professional knowledge of nutrition is necessary to decide daily recipes for improving health, it may be difficult for general users who do not have such knowledge to search for the right recipes. In this paper, we propose a goal-oriented recipe recommendation system that utilizes information about nutrition on the Internet....
Recently, there has been growing interest in understanding information cascading phenomenon on popular social networks such as Face book, Twitter and Plurk. The numerous diffusion events indicate huge governmental and commercial potential. People have proposed several diffusion and cascading models based on certain assumption, but until now we do not know which one is better in predicting information...
The estimation of biomass production of delta-endotoxins of the Bacillus thuringiensis (Bt) is a major problem in biotechnological processes, as bio-insecticides, which has been addressed with different methodologies such as extended Kalman filters (EKF), phenomenological observers, among others. This paper presents a comparison in the estimation of biomass concentration of delta - endotoxins of the...
An interactive image completion method is proposed based on Direction Empirical Mode Decomposition (DEMD). Blocked area or area with loss of information in a target image is completed with DEMD combined with texture synthesis in an interactive way. The target image is decomposed by DEMD into levels of Intrinsic Mode Functions (IMF) images, while the user is allowed to indicate the structural image...
Emotion modeling is a crucial part in modeling virtual humans. Although various emotion models have been proposed, most of them focus on designing specific appraisal rules. As there is no unified framework for emotional appraisal, the appraisal variables have to be defined beforehand and evaluated in a subjective way. In this paper, we propose an emotion model based on machine learning methods by...
New computing technologies, media acquisition/storage devices, and multimedia compression standards have increased the amount of digital data generated and stored by computer users. Nowadays, it is easy to access electronic books, electronic journals, and web portals, which contain tremendous graphics (drawings or diagrams) and images (pictures or scenery). Hence, it is imperative to develop an effective...
Interactions between people occur in a social realm. On the other hand, "things", including devices for communication and computation, are generally socially deficient. Imagine socially aware systems moving from an interruption model of communication to an introduction model. To create considerate systems, there is a need to model social context, social behavior, and communication goals...
Evolutionary robots have become an interesting topic recently. These robots can achieve certain goals via evolutionary algorithms without specifying all the detailed actions. The robot interacts with the environment and receives natural feedback from the environment regarding the fitness of its goal. In this paper, we study biomorphic robots. Our robots have three or four legs, and share the goal...
Video retrieval has been a hot topic due to the prevalence of video capturing devices and media-sharing services such as YouTube. Until now, few past studies has focused on querying the videos by images due to the semantic gap between images and videos is not easy to narrow. To this end, in this paper, we propose a novel semantic video retrieval system that integrates web image annotation and concept...
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