A Proposal of Back-Propagation Network for Recognizing Contact Character

A Novel Approach of Handwritten Devanagari Character Recognition through Feed Forward Back Propagation Neural Network

Handwritten character recognition plays an important role in the modern world. It can solve more complex problems and makes human’s job easier. The present paper portrays a novel approach in recognizing handwritten devanagari character through feed forward back propagation neural network. All the experiments are conducted by using the Artificial Neural Network tool of Matlab.

breathomics for gastric cancer classification using back-propagation neural network

breathomics is the metabolomics study of exhaled air. it is a powerful emerging metabolomics research field that mainly focuses onhealth-related volatile organic compounds (vocs). since the quantity of these compounds varies with health status, breathomics assuresto deliver noninvasive diagnostic tools. thus, the main aim of breathomics is to discover patterns of vocs related to abnormal metabo...

Feed Forward Back Propagation Neural Network based Character Recognition System for Tamil Palm Leaf Manuscripts

Optical character recognition refers to the process of translating segmented hand-written images or typewritten images into machine editable text. In this study, we propose a Tamil palm leaf manuscripts character recognition system using FFBNN technology. First the palm leaf manuscripts characters are segmented by exploiting the sliding window and adaptive histogram calculation. Afterwards, the...

Alternating Back-Propagation for Generator Network

This paper proposes an alternating back-propagation algorithm for learning the generator network model. The model is a nonlinear generalization of factor analysis. In this model, the mapping from the continuous latent factors to the observed signal is parametrized by a convolutional neural network. The alternating back-propagation algorithm iterates the following two steps: (1) Inferential back...

Recognizing Handwritten Digits Using the LLE Algorithm with Back Propagation