Balochi Non Cursive Isolated Character Recognition using Deep Neural Network

Cursive Character Segmentation Using Neural Network Techniques

Arabic Handwritten Alphanumeric Character Recognition Using Very Deep Neural Network

The traditional algorithms for recognizing handwritten alphanumeric characters are dependent on hand-designed features. In recent days, deep learning techniques have brought about new breakthrough technology for pattern recognition applications, especially for handwritten recognition. However, deeper networks are needed to deliver state-of-the-art results in this area. In this paper, inspired b...

Oiahcr: online isolated arabic handwritten character recognition using neural network

In this paper, an online isolated Arabic handwritten character recognition system is introduced. The system can be adapted to achieve the demands of hand-held and digital tablet applications. To achieve this goal, despite of single neural networks, four neural networks are used, one for each cluster of characters. Feed forward back propagation neural networks are used in classification process....

Character Recognition using Neural Network

Handwritten characters recognition (HCR) presents a great challenge in the field of image processing and pattern recognition. This paper presents handwritten English characters recognised using shape based zoning features with the help of neural network (NN) as a classifier. The neural network used is pattern-net. The recognition rate is observed almost 96%. .

Character Recognition Using Neural Network

In the present paper, we are use the neural network to recognize the character. In this paper it is developed 0ff-line strategies for the isolated handwritten English character (A TO Z) and (0 to 9) .This method improves the character recognition method. Preprocessing of the Character is used binarization, thresolding and segmentation method .The proposed method is based on the use of feed forw...