Gaussian Mixture Models As define in Wikipedia a Gaussian Mixture Model is a specific Mixture Model. “In statistics, a mixture model is a probabilistic model for representing the presence of subpopulations within an overall population, without requiring that an observed data set should identify the sub-population to which an...

Features extraction In all articles dealing with handwriting recognition, several steps are discussed and described in more or less detail. These are the preprocessing, the segmentation, the feature extraction, the classification and the post-processing. The purpose of preprocessing is to produce data adapted to the handwriting recognition system so...

Connectionist Temporal Classification After reading the paper from  Farès Menasri et al. “The A2iA French handwriting recognition system at the Rimes-ICDAR2011 competition”, we looked for inquiries about Connectionist Temporal Classification (CTC) as it is a really interesting method to label unsegmented sequences directly. In their article  Alex Graves, Santiago Fernández, Faustino...

Make predictions with a neural network. After building and evaluating neural network models let’s see how they behave to make predictions. We will evaluate model-by-model predictions and then use several training results and models with the bagging and voting method. Bagging and voting are popular methods for combining the...

Convolutional Neural Network Testing Now, we have some trained models and need to know how well they perform on unseen data. As, Dr.Jason Brownee wrote : “Why can’t you prepare your machine learning algorithm on your training dataset and use predictions from this same dataset to evaluate performance? The...