SIVARANJANE. R

To contribute to the organization to the best of my ability and to develop new skills and share my knowledge while interacting with my fellow teammates and achieve new heights. A Brief Overview A building professional with extensive conceptual knowledge in Information Technology and Systems. Exposure in end-to-end development of software products,right from requirement analysis, designing, coding, testing, documentation and implementation using diverse technologies. Resourceful in understanding of fundamental networking concepts pertaining to Data Stucture, LAN and WAN, information security,ITcommunication,troubleshooting and maintenance in multi-platform environments. Effective communicator with excellent relationship building & interpersonal skills;possesses a flexible &detailed oriented attitude with strong analytical, problem solving & organizational building abilities.

*Participated in various inter college symposiums.

 Worked as a class representative during my first semester.

* Was one of the Executive Members of the Paper Presentation team
in BITZ n BYTEZ’11, A National Level Technical Symposium in
our college.

 Attended national level conference and presented paper in the topic

BLUE EYE TECHNOLOGY

**I have attended Implant Training in JAVA and DOTNET Concepts

at HCL INFOSYSTEMS LTD

 Attended one day workshop on RECENT TRENDS IN NETWORK AND COMPUTER COMMUNICATION in our college.

 presented paper in the topic

TRAVEL PACKAGE RECOMMENDATION SYSTEM

Main project :
Title : PERFORMANCE ANALYSIS OF CLUSTERED MICROCALCIFICATIONS DETECTED ON MAMMOGRAMS
The project titled PERFORMANCE ANALYSIS OF CLUSTERED MICROCALCIFICATIONS DETECTED ON
MAMMOGRAMS.
The project is developed in MATLAB ,which is a new approach for classifications of mammogram images
in digital mammograms employing the various features set and KNN classifier. The system classifies the
mammogram images as normal or abnormal. Early detection and removal of the cancerous part is the
most effective way to cure the cancer. This suggests a texture based computerized analysis clusters of
microcalcification detected on mammograms in order to classify them into benign and malignant types.
The test of the proposed system yielded a sensitivity of 100%,a specificity of 87.7% and a good
classification rate of 89%.
Duration : 4 months
Team Strength : 3
Language : Matlab
Operating System : Windows Xp
Data base : MIAS(Mammography Image Analysis Society)

Declaration:

I,SivaRanjane.R, hereby declare that the above furnished information are authentic

to the best of my knowledge.

Date:20.06.2020

Place: Bengaluru