menu
{ "item_title" : "Kernel Learning Algorithms for Face Recognition", "item_author" : [" Jun-Bao Li", "Shu-Chuan Chu", "Jeng-Shyang Pan "], "item_description" : "Kernel Learning Algorithms for Face Recognition covers the framework of kernel based face recognition. This book discusses the advanced kernel learning algorithms and its application on face recognition. This book also focuses on the theoretical deviation, the system framework and experiments involving kernel based face recognition. Included within are algorithms of kernel based face recognition, and also the feasibility of the kernel based face recognition method. This book provides researchers in pattern recognition and machine learning area with advanced face recognition methods and its newest applications.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/1/49/395/212/1493952129_b.jpg", "price_data" : { "retail_price" : "119.99", "online_price" : "119.99", "our_price" : "119.99", "club_price" : "119.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Kernel Learning Algorithms for Face Recognition|Jun-Bao Li

Kernel Learning Algorithms for Face Recognition

local_shippingShip to Me
In Stock.
FREE Shipping for Club Members help

Overview

Kernel Learning Algorithms for Face Recognition covers the framework of kernel based face recognition. This book discusses the advanced kernel learning algorithms and its application on face recognition. This book also focuses on the theoretical deviation, the system framework and experiments involving kernel based face recognition. Included within are algorithms of kernel based face recognition, and also the feasibility of the kernel based face recognition method. This book provides researchers in pattern recognition and machine learning area with advanced face recognition methods and its newest applications.

This item is Non-Returnable

Details

  • ISBN-13: 9781493952120
  • ISBN-10: 1493952129
  • Publisher: Springer
  • Publish Date: August 2016
  • Dimensions: 9.21 x 6.14 x 0.51 inches
  • Shipping Weight: 0.76 pounds
  • Page Count: 225

Related Categories

You May Also Like...

    1

BAM Customer Reviews