Name: Pattern Recognition And Classification: An Introduction (en Inglés)
Price: 544.93 PEN
Availability: InStock
Author: Dougherty, Geoff
ISBN: 9781493953356

portada Pattern Recognition And Classification: An Introduction (en Inglés)

Formato

Libro Físico

Autor

Geoff Dougherty

Editorial

Springer

Año

2017

Idioma

Inglés

N° páginas

196

Encuadernación

Tapa Blanda

Dimensiones

23.4 x 15.6 x 1.1 cm

Peso

0.30 kg.

ISBN13

9781493953356

Categorías

Teoría del caos
Ingeniería electrónica
Reconocimiento de formas
Visión por ordenador

Pattern Recognition And Classification: An Introduction (en Inglés)

Geoff Dougherty (Autor) · Springer · Tapa Blanda

Libro Nuevo

S/ 544,93

S/ 1.089,87

Ahorras: S/ 544,93

50% descuento

Envío normal

Origen: Estados Unidos (Costos de importación incluídos en el precio)

Se enviará desde nuestra bodega entre el Lunes 17 de Junio y el Lunes 01 de Julio.

Lo recibirás en cualquier lugar de Perú entre 2 y 5 días hábiles luego del envío.

Reseña del libro "Pattern Recognition And Classification: An Introduction (en Inglés)"

The use of pattern recognition and classification is fundamental to many of the automated electronic systems in use today. However, despite the existence of a number of notable books in the field, the subject remains very challenging, especially for the beginner. Pattern Recognition and Classification presents a comprehensive introduction to the core concepts involved in automated pattern recognition. It is designed to be accessible to newcomers from varied backgrounds, but it will also be useful to researchers and professionals in image and signal processing and analysis, and in computer vision. Fundamental concepts of supervised and unsupervised classification are presented in an informal, rather than axiomatic, treatment so that the reader can quickly acquire the necessary background for applying the concepts to real problems. More advanced topics, such as semi-supervised classification, combining clustering algorithms and relevance feedback are addressed in the later chapters. This book is suitable for undergraduates and graduates studying pattern recognition and machine learning.