Mrs. S. Latha M.E (CSE) (Ph.d)

I'm Assitant Professor.

About

Mrs.S.Latha M.E(Computer Science And Engineering), is working as Assistant Professor in the department Of Information Technology, Mahendra Engineering College (Autonomous) and Pursuing Ph.D degree (PT) , research in the area of medical image processing under the recognition of Anna University since July 2018. I have Secured GATE Score: 430 (Computer Science and Engineering) in 2015 and Freelancer of GATE Examinations.

Assistant Professor

Mrs.S.Latha M.E(Computer Science And Engineering),has published around 20 research papers in journals and conferences under various research areas like image processing, cloud computing etc., and published three books under magnus publication.

  • Birthday: 03.10.1980
  • Department: Information Technology
  • Phone: 7010911309
  • Specialization Computer Science & Engineering
  • Age: 45
  • Degree: Master
  • Email: lathas@mahendra.info,lathakvpudur@gmail.com
  • Teaching Experience: 18 Yrs 2 Months

Mrs.S.Latha M.E(Computer Science And Engineering), has organized various events like workshop, symposium and conferences and received Certificate of Recognition from InfosysCampus connects Programme and Certified trainer for the course “IBM DB2 Academic Associate: DB2 Database and Application Fundamentals”. I have received mentor certificate from NPTEL and used to learn NPTEL course regularly as a continuous learner. Life Member of ISTE. I am interested to learn recent trends like machine learning ,deep learning and Data Science.

Teaching Experience

Published Papers

Gate Score

published books

Phd(Registered - July 2018 Session)

Research Degree

Ph.D

Innovative and results-driven Deep Learning Researcher with expertise in developing advanced AI-driven frameworks for medical and environmental applications. Proven track record in designing high-precision models for disease classification by delivering cutting-edge solutions from concept to deployment.

Hexa Classification of Erythemato Squamous Disease using Deep Dual Features based Neural Network

Abstract:Deep learning-based Hexa-ESD framework for classifying six types of erythemato-squamous diseases (ESD) using clinical skin images. The methodology involves denoising using an advanced filter, feature extraction via hybrid Deep learning Network, feature selection using the bio-inspired Optimization algorithm, and classification with a Deep Belief Network (DBN). Our research highlights the effectiveness of advanced deep learning and optimization techniques in dermatological diagnosis.

Research Publication 1
Training Attended 20
presentations in Conferences / Seminars / Workshops 12
Seminars, Conferences, Symposia Workshops 10
Membership in M-ISTE Yes
Published Papers 20

PHD Work

Self prepared ESD_348 dataset consists of clinical skin images gathered from various sources, including Kaggle and the UCI repository. The images are labeled based on the structured categorization of the UCI repository.

Download Self prepared ESD_348
  • About Self Prepared ESD_DATASET_348
  • Content
  • Acknowledgements

  • Dataset name:Self prepared ESD_348

  • Disease name:Erythemato Squamous Disease

  • Number of classes :6

  • Number of images :348

The dataset includes 366 observations with 12 clinical features and 6 classes of skin diseases: psoriasis, seborrheic dermatitis, lichen planus, pityriasis rubra pilaris, chronic dermatitis, and rosea. Our self-prepared dataset depends on the Kaggle dataset, we have gathered the clinical skin images from this dataset and labeled them based on the UCI repository. All the six classes are represented owing to the 155 images provided by UCI and the 193 images contributed by Kaggle. The distribution reflects class-specific totals while keeping data sources balanced. The target variables were six classes and the number of instances in each class includes psoriasis (111 cases), seborrheic dermatitis (52 cases), lichen planus (71 cases), pityriasis rubra pilaris (20), chronic dermatitis (46), and rosea (48) respectively.

We acknowledge the sources of our dataset, including the Kaggle dataset and the UCI repository by providing valuable resources for our research.

Education

Sumary

Mrs.S.Latha M.E(Computer Science And Engineering)

working as Assistant Professor in the department Of Information Technology, Mahendra Engineering College (Autonomous) and Pursuing Ph.D degree (PT) , research in the area of medical image processing under the recognition of Anna University since July 2018.

  • Computer Science & Engineering
  • 7010911309
  • lathas@mahendra.info

Education

High School

1996

State Board , Government High School, Rasipuram

Maths, Science & Social Science

91.2 %

Pre-Degree

1998

State Board, Government Higher Secondary School, Rasipuram.

Maths, Physics, Chemistry , Computer Science

88.25 %

Professional Experience

Assistant Professor

2010 - Present

Mahendra Engineering College (Autonomous)

  • 18+ years of academic Experience
  • Gate Scorer.

Higher Education

Bahelor’s Degree

2002

Tamilnadu College Of Engineering , Coimbatore. Bharathiar University

  • Computer Science & Engineering
  • 81.5& First Class With Distinction.

Master’s Degree

2010

Sapthagiri Engineering College ,Dharmapuri. Anna university , Chennai

  • Computer Science & Engineering
  • 9.14&& First Class With Distinction