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ANBUMANI ARUMUGAM

ANBUMANI ARUMUGAM

ASSISTANT PROFESSOR · COMPUTER SCIENCE AND ENGINEERING
Author
APID
4869
ORCID
0000-0002-2632-6012
Google Scholar
anbuinfo2006@gmail.com
Location
NAMAKKAL, Tamil Nadu, India
Expertise
i am interested reviewer and editor in journal.
Areas of interest
Medical image processing, Data Science, Bigdata
Member since
November 2023

Biography

Prof.A.Anbumani. doing research in Information and Communication Engineering from Anna University, Chennai, as a part time Research Scholar. He is having 15 years and 3 months of teaching experience. His specialized areas include medical imaging and Bio Medical Image Processing. He has published over 17 papers in the refereed national, international journals and conferences.
 2 Years of Experience in developing applications using JAVA/J2EE Technologies.
 Excellent Programming and Analytical Skills.
 Last institution I had worked as a Naac Criteria 3, Gate exam, Academic Calendar, Student Feedback form, Parent’s and Teacher feedback form, Intra Faculty Seminar , Higher studies Details, TDS form, Faculty Personal Profile, Sports and Culture, Stock details (note book requirement) in KNCET 2022 to 2023.
 I have worked as IIC Coordinator and IIPC Coordinator in ESEC 2021 to 2022.
 Overall Placement co-coordinator with Student Support Team (SST) in MIT 2015 to 2019.
 Admission Counselor in MIT 2014-2015.
 Last nine years, I had put it admission 100+ students. (59 Engineering, 32 Arts, 1 Poly,1 Bds, 1 Pharmachy,1 Nursing, 5 International school, 1 later entry).
 Two year back, I have in NAAC coordinator. (Placement, Training, Club Activity and Mentor systems) in MIT.
 Now I have Placement ,Naan Mudhalvan and Naac Criteria 5 co-ordinar in PCE.

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Publications

  1. Book : 1. Handbook of research in Big data Analytics, Artificial Intelligence and Machine Learning -CHAPTER 48 " A Review On Skin Cancer Disease Detection"
  2. Breast Cancer Accuracy Level Detection Using Transfer Learning
  3. CLASSIFICATION AND IDENTIFICATION OF BLB USING ARTIFICIAL NEURAL
  4. Classification of Mammogram Images Using Multi-SVM
  5. Diagnosis Of Heart Disease Using Machine Learning Classification Technique In E-Healthcare
  6. Mammogram breast cancer segmentation and classification usingHierarchical Fuzzy C Means – Modified Expectation Maximization algorithm and deep convolutional neural network