Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Taschenbuch. Zustand: Neu. Neuware -This book critically reviews the various soft computing techniques employed in handwriting recognition and presents recognition accuracy achievements available in the literature. With advancements in the areas of artificial intelligence and machine learning, the expectation and challenges in handwriting recognition have become more and more demanding. The focus of this book is to explore the various steps involved in a handwriting recognition system such as pre-processing, feature extraction, feature selection and classification. Soft computing techniques such as neural network, fuzzy logic, genetic algorithm and neuro-fuzzy are applied in the recognition process. Some attempts based on hybrid feature extraction, GA based feature subset selection, ranking based feature selection methods, and optimization of learning parameters are also employed for further improvement in the recognition accuracy. 208 pp. Englisch.
Anbieter: Books Puddle, New York, NY, USA
Zustand: New.
Anbieter: Buchpark, Trebbin, Deutschland
Zustand: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | This book critically reviews the various soft computing techniques employed in handwriting recognition and presents recognition accuracy achievements available in the literature. With advancements in the areas of artificial intelligence and machine learning, the expectation and challenges in handwriting recognition have become more and more demanding. The focus of this book is to explore the various steps involved in a handwriting recognition system such as pre-processing, feature extraction, feature selection and classification. Soft computing techniques such as neural network, fuzzy logic, genetic algorithm and neuro-fuzzy are applied in the recognition process. Some attempts based on hybrid feature extraction, GA based feature subset selection, ranking based feature selection methods, and optimization of learning parameters are also employed for further improvement in the recognition accuracy.
Anbieter: Buchpark, Trebbin, Deutschland
Zustand: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | This book critically reviews the various soft computing techniques employed in handwriting recognition and presents recognition accuracy achievements available in the literature. With advancements in the areas of artificial intelligence and machine learning, the expectation and challenges in handwriting recognition have become more and more demanding. The focus of this book is to explore the various steps involved in a handwriting recognition system such as pre-processing, feature extraction, feature selection and classification. Soft computing techniques such as neural network, fuzzy logic, genetic algorithm and neuro-fuzzy are applied in the recognition process. Some attempts based on hybrid feature extraction, GA based feature subset selection, ranking based feature selection methods, and optimization of learning parameters are also employed for further improvement in the recognition accuracy.
Anbieter: moluna, Greven, Deutschland
EUR 64,09
Anzahl: Mehr als 20 verfügbar
In den WarenkorbZustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Ahlawat SavitaDr Savita Ahlawat is currently working as a Reader (CSE Dept.) at MSIT, New Delhi. She has done B.E., M.Tech.(IT) & Ph.D. (CSE) and holds 15 years of teaching experience. She has published around 25 papers in internatio.
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
EUR 130,33
Anzahl: 4 verfügbar
In den WarenkorbZustand: New. Print on Demand.
Anbieter: preigu, Osnabrück, Deutschland
Taschenbuch. Zustand: Neu. Optimal Handwriting Recognition Using Soft Computing Techniques | Design and Implementation | Savita Ahlawat | Taschenbuch | 208 S. | Englisch | 2019 | Scholars' Press | EAN 9786138839149 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu Print on Demand.
Anbieter: Biblios, Frankfurt am main, HESSE, Deutschland
Zustand: New. PRINT ON DEMAND.
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book critically reviews the various soft computing techniques employed in handwriting recognition and presents recognition accuracy achievements available in the literature. With advancements in the areas of artificial intelligence and machine learning, the expectation and challenges in handwriting recognition have become more and more demanding. The focus of this book is to explore the various steps involved in a handwriting recognition system such as pre-processing, feature extraction, feature selection and classification. Soft computing techniques such as neural network, fuzzy logic, genetic algorithm and neuro-fuzzy are applied in the recognition process. Some attempts based on hybrid feature extraction, GA based feature subset selection, ranking based feature selection methods, and optimization of learning parameters are also employed for further improvement in the recognition accuracy.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 208 pp. Englisch.
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book critically reviews the various soft computing techniques employed in handwriting recognition and presents recognition accuracy achievements available in the literature. With advancements in the areas of artificial intelligence and machine learning, the expectation and challenges in handwriting recognition have become more and more demanding. The focus of this book is to explore the various steps involved in a handwriting recognition system such as pre-processing, feature extraction, feature selection and classification. Soft computing techniques such as neural network, fuzzy logic, genetic algorithm and neuro-fuzzy are applied in the recognition process. Some attempts based on hybrid feature extraction, GA based feature subset selection, ranking based feature selection methods, and optimization of learning parameters are also employed for further improvement in the recognition accuracy.