Tuan Trung Nguyen

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Classification systems working on large feature spaces, despite extensive learning, often perform poorly on a group of atypical samples. The problem can be dealt with by incorporating domain knowledge about samples being recognized into the learning process. We present a method that allows to perform this task using a rough approximation framework. We show(More)
Optical Character Recognition (OCR) is a classic example of decision making problem where class identities of image objects are to be determined. This concerns essentially of finding a decision function that returns the correct classification of input objects. This paper proposes a method of constructing such functions using an adaptive learning framework,(More)
This paper summarizes the some of the recent developments in the area of application of rough sets and granular computing in hierarchical learning. We present the general framework of rough set based hierarchical learning. In particular, we investigate several strategies of choosing the appropriate learning algorithms for first level concepts as well as the(More)
PURPOSE In forensic investigations, crime scene reconstructions are created based on a variety of three-dimensional image modalities. Although the data gathered are three-dimensional, their presentation on computer screens and paper is two-dimensional, which incurs a loss of information. By applying immersive virtual reality (VR) techniques, we propose a(More)
We have revised the manuscript and references. Last revision of the manuscript was made by two native English speakers, (not this letter). We have corrected all the errors listed, and made all the requested clarifications by reviewers. Some paragraphs have been modified. You will find below a point by point reply, and details of these changes, according to(More)