Research

Whatever knowledge I have gained on this journey is credited to Professors from the University of Mysore, Professor K. Revathy from the University of Kerala, Professor Anurag Tyagi from Chinmaya Institute, Professor Ganesan K. from VIT, and my PhD supervisor, Professor Dugki Min: प्रणमाम


PhD Student 

1. Anjali T (2022- ~) Amrita Vishwa Vidyapeetham 

Area of focus: Video Anomaly Detection  

         Yearly status- 2023 

  2. P Ashok Kumar(2015 - 2021)  VIT Vellore

     Area of Interest: High Dimensional  Data Visualization 

   Published Papers

Research Associates and Undergraduate Students

1.  Rishabh Saxena  VIT

Area of Interest : Image Classification and CNN 

B.Tech Project Title : Analyzing Deep Learning Techniques for Image and Vision Techniques: How Capsule Networks are the new iteration in Object Detection  

 Amit Adate, Rishabh Saxena, S Don, "Understanding How Adversarial Noise Affects Single Image Classification ", International Conference on Intelligent Information Technologies,2018

Amit Adate, Rishabh Saxena, S Don,"A comparative study on Adversarial Noise Generation for Single Image Classification ", International Journal of Intelligent Information Technologies,2020.(Index SCI-E IF : 0.326) 

2. Deepika S   and Elangovan K      VIT

Cheif Mentor : Senior Prof : Ganesan K 

S. Deepika, Elangovan K, Don S, Lekshmi S, Ganesan K, " Tiling algorithm with line-based transform for rapid ship detection and wake feature extraction in ALOS-2 SAR sensor data",  International Journal of Applied Science and Engineering, 19,2022

3. Shaik Mohammad, T Anil, GH Sai Keertan and Satwik Tangudu   Amrita Vishwa Vidyapeetham 

Shaik Mohammad, T Anil, GH Sai Keertan and Satwik Tangudu,"Traffic Sign Detection Using SSD  Mobilenet & Faster RCNN" 2nd  IEEE VITeCON,2023

4. Sanjay Raju,Nandakishor S, Sreerag K Vivek : Amrita Vishwa Vidyapeetham ,"Deep Learning Techniques for Crater Detection on Lunar Surface Images from Chandrayaan-2 Satellite" ,Journal of the Indian Society of Remote Sensing  (Submitted May 2023 , accepted on June -2024)

5. Dhanvanth Reddy Yerramreddy, Veerababu Addanki , Sathvik Durgapu Amrita Vishwa Vidyapeetham

Dhanvanth Reddy Yerramreddy, Veerababu Addanki , Sathvik Durgapu ,"Analysis of Image Restoration techniques on Lunar Surface Images", iPACT, 2023 

Dhanvanth Reddy Yerramreddy, Veerababu Addanki , Sathvik Durgapu ,"Gaze Estimation Using VGG16 Architecture Through XGBoost Classifier",5th IEEE ICECIE,2023 

6.Guggilam Sai Prabhat, Nehith Sai Vemulapali, Paladugula Pruthvi  Amrita Vishwa Vidyapeetham

Reinforcement Learning-Based Autonomous Landing of AirSim Simulated Quadcopter in Unreal Engine, 2024

Research Profile 

    Orcid   Scopus  ResearchID  Google Scholar

Membership / Achievements 

      Associate Editor for an SCI Indexed journal, and reviewer for more than 15 journals  

      Biographical Nominated in " Marquis Who's Who "  ,

      Institute of Information Technology Advancement , Korean Govt Scholarship (2008-2012), S.Korea 

  Ongoing Research Work

       Image Analysis - remote sensing and medical 

           Members : Sanjay Raju,Nandakishor S and Sreerag K Vivek, Dhanvanth Reddy Yerramreddy,       

                                Veerababu Addanki , Sathvik Durgapu      

          Scailable drone architecture -  navigation 

           Members : Santosh and Gagan  

Previous Research Work

      Mammogram image segmentation

      Image analysis based on Semantics

      Electrocardiogram signal Classification

      Developed middleware  technologies for self-awareness systems

      Semantic Representation and Annotation of Medical Information and Symptom Retrieval   

Technical Expertise

        Matlab, Simulink, Protégé, SPARQL, Apache Jena, OSGi framework, Dempsy framework ,WSO2 Framework and CEP  

Future Research Areas 

       AI in Behavioral Science 

Interesting Materials

Research Evaluation Matrix   Eigen factor for evaluation 

Reporting a Self-Citation Index

Personalized Healthcare- Next Generation HMS !!!

Talking Architects with Len Bass

Difference between Ontologies and Database Schema  PPT

Awareness Magazine

Situation Awareness and CEP

Advice For PhD students By Philip Torr's  

Advice For PhD students by Charles X Ling's

Reading for Graduate Students

Five Important Machine Learning Books 

 Alpaydin, Introduction to Machine Learning. 

 David Barber, Bayesian Reasoning and Machine Learning.  

 Kevin P. Murphy, Machine Learning: A Probabilistic Perspective .

 Christopher M. Bishop, Pattern Recognition and Machine Learning.

 Peter Flach, Machine Learning: The Art and Science of Algorithms that Make Sense of Data

Foundation 

Serge Lang, Introduction to Linear Algebra.

Lloyd Trefethen, Numerical Linear Algebra.

Gilbert Strang, Linear Algebra and Its Applications. 

Gene Golub and Charles Van Loan, Matrix Computations.

Kaare Brandt Petersen Michael Syskind Pedersen, The Matrix Cookbook

 Funded Projects

 Patents Granted   

 

Journal Publication

Book Chapters and Conference Publication

 QIP Program Attended 

PostDoctoral Fellow

Worked with Prof. Dugki Min, Konkuk University. S.Korea

Project Title : Patent Document Neutralization Based on Semantics and Data Mining Techniques

Type of research: Product Development Research 

Publication : Korean IPC 

Ph.D. Course Work (GPA 4.12/4.5) 

Semester 1 :

Semester 2:

Semester 3:

Semester 4:

Ph.D in Computer Science (2008~2013 Full-Time)   @ Dept of Computer Science and Engineering 

Dissertation Title: Medical Information Analysis and Abnormality Awareness Service Framework 

Examination Panel : Prof. Kyoungro Yoon(Chair), Prof. HeonChang Yu(External examiner) , Prof. Young-guk Ha(Internal examiner), Prof. Choi Eunmi(External examiner), Prof. Dugki Min(Internal examiner and Supervisor)

MTech  in Computer Cognition Technology (GPA 4.06/5)

Semester Work

Semester  1 :

Semester 2:

Semester 3:

Minor Project  Internal Guide ( Dr. Lalitha Rangarajan  and  Prof. K Revathy )

Semester 4:

Major Project  Intenal Guide ( Prof. DS Guru and Prof K.Revathy )

MTech Thesis : Classifying Images Using Fractal Features

The aim of this research work is to classify remotely sensed data using fractal features. For recognition of regions and object in natural scenes, there is always a need for features, which are invariant and they provide a good set of descriptive value for the region. There are numerous methods available to estimate parameters from image of fractal surface. Fractal features can be used for classifying images. A very general technique to calculate numerous fractal features involve the estimation of the mass density functions by box counting. Fractal dimension provides a powerful means for analyzing and extracting various features from the image. Fractal dimension and fractal signature are used to characterize the degree of self-similarity among the degree of self-similarity among the point in the image.

Supervisor    : Prof  K.Revathy and Prof DS Guru

Organization : Dept of Computer Science, University of Kerala

Language      : Matlab 6.1

MSc Thesis:   Lan Manager

 Lan Manager enables the local network administrator to perform real-time monitoring, data analysis and transmission. Here the administrator monitors all the users logged on to the network. Security features are also enhanced in to software by checking username and password. Advantage offered by networking system include high-speed data transfer .The administrator’s job is made easier. Concepts of compression, decompression, multithreading and socket programming are used here. This project will help the user to reduce more of manual work. It saves more time and generates various conclusions within seconds. Message transfers can be done within the click of a mouse. Thus making the work easier.

Front End Tool : VC++6.0

Undergraduate Students