Afra Shams

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This paper proposes a new classification method for Farsi handwritten word recognition using gradient and gradient based features. The extracted feature vectors were classified using two Multi Layer Perceptron networks as basic experts, and one Radial Basis Function was applied to choose the best expert. The experiments were performed using the Iranshahr(More)
This paper investigates Farsi handwritten word recognition using common features. Also we applied biologically inspired features (BIFs), derived from a feed forward model of object recognition pathway in visual cortex for Farsi handwritten word recognition problem. Experimental results show that the model achieves high recognition percentage even for large(More)
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