REMYA S S BIO-DATA

  • : 9746486712
  • : ssremyass@gmail.com

A challenging position in a competitive environment where I enhance my skills and strengths in conjunction with the companies’ goals and objectives And the strong thing in me is that the way i use my logical solutions which is damnedest. I believe to work with team.

Education

SSLC – GOVT. VOCATIONAL HIGHER SECONDARY SCHOOL, PARASSALA

May 2007 - March 2008
I COMPLETED SSLC WITH FIRST CLASS

PLUS TWO – EVANS HIGER SECONDARY SCHOOL PARASSALA

June 2008 - March 2010
I COMPLETED PLUS TWO WITH FIRST CLASS

B-TECH – K R GOURI AMMA COLLEGE OF ENGINEERING FOR WOMEN,THURAVOOR,ALAPPUZHA

May 2010 - April 2014
I COMPLETED B-TECH DEGREE COURSE WITH FIRST CLASS

M-TECH – LORDES MATHA COLLEGE OF SCIENCE AND TECHNOLOGY, KUTTICHAL P O , THIRUVANANTHAPURAM

Aug 2015 - Present
STILL I STUDYING

Project

EXPERT PEER CONNECT

Skills : ANDROID , JAVA
EXPERT PEER CONNECT : LIFE TIME

As we know that current communication technology is moving to tablets and I-phones it is important to notice the rapid change in the era. So as part of that to give technical expert support in the android devices as a first step we are proposing a system" Expert Peer Connect ", which is a remote access to an android device from another android device via Wi-Fi. " Expert Peer Connect " is a system that enables a technical expert or other android user to access an android device remotely via Wi-Fi.

DENSE REGION DETECTORS FOR IMAGE SEARCH AND FINE-GRAINED CLASSIFICATION

Skills : .NET , C#
DENSE REGION DETECTORS FOR IMAGE SEARCH AND FINE-GRAINED CLASSIFICATION : LIFE TIME

In the context of image classification or search based on coding approaches like bag of words or Fisher vectors, the most common approach is to extract the image patches regularly in a dense manner on several scales. This paper proposes and evaluates alternative choices to extract patches densely. Beyond simple strategies derived from regular interest region detectors, this paper propose approaches based on superpixels, edges, and a bank of Zernike filters used as detectors. The different approaches are evaluated on recent image retrieval and fine-grained classification benchmarks. Results show that the regular dense detector is outperformed by other methods in most situations, leading us to improve the state-of-the-art in comparable setups on standard retrieval and fined-grained benchmarks. As a byproduct of study, I show that existing methods for blob and superpixel extraction achieve high accuracy if the patches are extracted along the edges and not around the detected regions.

Skills

  • M S OFFICE

Personal Details

  • Father Name

    SASI C
  • Address

    PODUVALVILA HOUSE, AYIRA P O, PARASSALA , THIRUVANANTHAPURAM , KERALA , INDIA , 695502
  • DOB

    11-Sep-1992
  • Language

    ENGLISH , MALAYALAM , HINDI , TAMIL
  • Hobbies

    LISTENING MUSIC, PLAYING BOARD GAMES, READING BOOKS, GARDENING