Andere Kunden interessierten sich auch für
![Machine Learning Techniques for Bird Sound Classification]( "Machine Learning Techniques for Bird Sound Classification")
Machine Learning Techniques for Bird Sound Classification44,99 €![Approach for Prediction of Heart Diseases by Rough Fuzzy Classifier]( "Approach for Prediction of Heart Diseases by Rough Fuzzy Classifier")
Approach for Prediction of Heart Diseases by Rough Fuzzy Classifier46,99 €![Computational Intelligence Paradigms in Advanced Pattern Classification]( "Computational Intelligence Paradigms in Advanced Pattern Classification")
Computational Intelligence Paradigms in Advanced Pattern Classification74,99 €![Intertwining Graphonomics with Human Movements]( "Intertwining Graphonomics with Human Movements")
Intertwining Graphonomics with Human Movements55,99 €![Ansatz zur Vorhersage von Herzkrankheiten durch Rough Fuzzy Classifier]( "Ansatz zur Vorhersage von Herzkrankheiten durch Rough Fuzzy Classifier")
Ansatz zur Vorhersage von Herzkrankheiten durch Rough Fuzzy Classifier71,90 €![Strength or Accuracy: Credit Assignment in Learning Classifier Systems]( "Strength or Accuracy: Credit Assignment in Learning Classifier Systems")
Strength or Accuracy: Credit Assignment in Learning Classifier Systems125,99 €![Graphonomics in Human Body Movement. Bridging Research and Practice from Motor Control to Handwriting Analysis and Recognition]( "Graphonomics in Human Body Movement. Bridging Research and Practice from Motor Control to Handwriting Analysis and Recognition")
Graphonomics in Human Body Movement. Bridging Research and Practice from Motor Control to Handwriting Analysis and Recognition43,99 €
The technological advances and the massive flood of papers have motivated many researchers and companies to innovate new methods and technologies. They build automatic readers to recognize handwritten documents. In particular, handwriting recognition is very useful technology to support applications like electronic books (eBooks), postcode readers (that sort the mail in post offices), and some bank's applications. This book proposed systems to discriminate handwritten graffiti digits and some commands with different architectures and abilities. It introduced three classifiers, namely single neural network (SNN) classifier, parallel neural networks (PNN) classifier and tree-structured (TS) classifier. The three classifiers have been designed through adopting feed-forward neural networks. The back-propagation algorithm has been used to optimize the network's parameters (connection weights). Several architectures are applied and examined to present a comparative study about the three systems from different perspectives.