Fr. 57.50

Deep Face Technique for Facial Recognition - Using Neural Network. DE

English · Paperback / Softback

Shipping usually within 2 to 3 weeks (title will be printed to order)

Description

Read more

The most recent decade has seen a pattern towards an inexorably universal nature, where compelling and minimal effort registering frameworks are, no doubt coordinated into cell telephones, autos, therapeutic instruments and very nearly every part of our lives. Face recognition is an assignment that people perform routinely and easily in their everyday lives. The performance process of face recognition involves the inspection study of facial features in an image, recognizing those features and comparing them to one of the many faces in the database. There are many algorithms capable of performing face recognition; such as: Principal Component Analysis, Discrete Cosine Transform, 3D recognition methods, Gabor Wavelets method etc. Significance of face acknowledgment frameworks have velocity up in the most recent couple of decades.

About the author










Gurpreet Kaur, Coordinator of School & Assistant Professor (Agriculture) School of Agriculture & Natural Sciences, CT University, Punjab.Jimmy Singla, Professor & Head of School of Engineering and Technology, CT University, Punjab.Danish Meiraj, Working as an Assistant Professor - School of Engineering and Technology, CT University, Punjab.

Product details

Authors Abhishek Bhardwaj, Gurpreet Kaur, Amarpreet Singh
Publisher LAP Lambert Academic Publishing
 
Languages English
Product format Paperback / Softback
Released 07.06.2023
 
EAN 9786206178798
ISBN 9786206178798
No. of pages 60
Dimensions 150 mm x 3 mm x 220 mm
Weight 98 g
Subjects Guides
Natural sciences, medicine, IT, technology > IT, data processing

Customer reviews

No reviews have been written for this item yet. Write the first review and be helpful to other users when they decide on a purchase.

Write a review

Thumbs up or thumbs down? Write your own review.

For messages to CeDe.ch please use the contact form.

The input fields marked * are obligatory

By submitting this form you agree to our data privacy statement.