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This paper proposes an intellectual classification system to recognize normal and abnormal MRI brain images. Nowadays, decision and treatment of brain tumors is based on symptoms and radiological appearance. Magnetic resonance imaging (MRI) is a most important controlled tool for the anatomical judgment of tumors in brain. In the present investigation, various techniques were used for the classification...
In this paper, a computationally efficient approach to transcription of monophonic melodies from a raw acoustic signal is presented. Two different instance-based pitch classification methods are proposed, the choice of which depends on the size of the available training database. In the first method, the conventional K-Nearest Neighbor algorithm is trained on a large database of piano tones and employed...
In this paper, a compensatory neurofuzzy inference system (CNIS) is proposed for classification applications. The compensatory-based fuzzy reasoning method using adaptive fuzzy operations of neurofuzzy inference systems makes fuzzy logic systems more adaptive and effective. Furthermore, an online learning algorithm is proposed to automatically construct the CNIS model. They are created and adapted...
This paper presents a novel 3D surface texture classification method based on self-similarity maps which are calculated directly from raw captured texture images. 3D surface textures have special properties for they are sensitive to illumination and view conditions. Some previous classification methods which are illumination invariant or rotation invariant have shown to be effective to this particularity,...
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