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The 3D object recognition stands a very important role in the process of computer vision. The recognition of objects is fundamental step in the design of more automated systems. The need for these systems is now high. Therefore, the 3D object recognition has a high impact. The most frequently used methods are based on neural networks (NNs), or, the derivation of NNs. The NNs approaches have high impact...
Recognition of complex language objects is a proposition for human-like perception of the surrounding world by machines. The crucial complication is a high complexity of relationships that may arise in the recognition of these objects. This implies existence of a high variety of approaches for perceived image objects recognition. One of the approaches, to which also this paper is devoted, is based...
In this paper, we focus on shape based grammar design. Our goal is to create a grammar that is capable to describe shapes occurring on images. Words in the language generated by this grammars are composed of direction vectors. We explore possibilities of these grammars. We focus on these several aspects: grammar determinism, cyclicality of language words and level of resistance towards deformation...
We introduce the principles of symbolization and conceptualization of perceived reality. We show them as processes that are applicable inside of a computer mind. We derive those processes from principles of a human mind. We present process of higher order regular abstraction and state automata acceptance as possible machine reality realization mechanism. We present the algorithm for evolution of machine...
Finding a method which allows a computer recognition to be close to human recognition is a goal of many works in the present. We have set this goal too. According to us, we need to find function for simple recognition of shapes in the images as first step of this goal. Result of this method provides input of our system of recognition. System form depends on the result of shape recognition method....
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