Saturday 18 June 2016

Face Detection using Hadoop MapReduce Framework


Face detection  is a PC innovation that is utilized to spot and distinguish human appearances in computerized pictures. Programming and particular calculations are utilized to build up the presence, area, size and different points of interest of a human face in a photo or video or some other picture. The product has the capacity to separate between the facial elements of the individual and other foundation objects.

Go along with this online course to figure out how to distinguish and separate appearances from pictures utilizing the Hadoop MapReduce structure. Hadoop MapReduce is a standout amongst the most sought after programming models that attempts to actualize preparing and producing tremendous information sets with parallel and appropriated calculations on a bunch. A MapReduce program basically comprises of a Map, the methodology that channels and sorts information, and a Reduce, which plays out the synopsis operation, along these lines actualizing the MapReduce System foundation or structure that coordinates the information handling by marshaling appropriated servers, running parallel assignments, dealing with all information exchanges between framework parts and minimizing redundancies and issues.

The center of this online course is the anaylsis of unstructured information utilizing the Hadoop Framework. Specifically it will focus on face location by means of Hadoop Framework. The online class will incorporate hypothesis furthermore have a hands-on down to earth session. In this online class will take you through the fundamental parts of Hadoop MapReduce and afterward talk about a portion of the picture handling calculations. It will likewise display a basic model that can be utilized for the recognition, area and extraction of countenances from pictures in the Hadoop Framework with the assistance of particular calculations.

Webinar Details-

Webinar Topic- Face Detection Using Hadoop Mapreduce Framework
 Date:                21 June 2016 at 6:30 Pm (IST)
Register For Webinar- http://goo.gl/2bW2Wk





0 comments:

Post a Comment