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Dr. Gopakumar G.

Assistant Professor (Selection Grade), School of Computing, Amritapuri

Qualification: B. Tech., M.Tech., Ph.D
gopakumarg@am.amrita.edu
ORCID Profile
Google Scholar Profile
ResearchGate Profile
Scopus Author ID
Research Interest: Computer Vision, Image Analysis, Machine Learning

Bio

Dr. G Gopakumar joined the Department of Computer Science and Engineering in June 2006 and is currently working as Assistant Professor (Selection Grade). He is a post-graduate (M.Tech.) in Digital Image Computing from the Department of Computer Science, University of Kerala (Karyavattom Campus) and a graduate (B.Tech.) in Computer Science and Engineering from the College of Engineering, Karunagappally (then affiliated to Cochin University of Science and Technology). Dr. Gopakumar pursued his Ph. D. from the Indian Institute of Space Science and Technology in Computer Vision (Medical Image Analysis) under the guidance of Dr. Gorthi R. K. Sai Subrahmanyam. His research thesis is ‘Automatic Feature Extraction and Classification of Cell images for Cytopathology.’ His research interests include Image Analysis and Machine Learning, and he has published many Scopus-indexed research articles, including Tier-1 Journals, Book Chapters, and Conference Publications.

Publications

Journal Article

Year : 2023

Saliency and ballness driven deep learning framework for cell segmentation in bright field microscopic images

Cite this Research Publication : SB Asha, G Gopakumar, GRKS Subrahmanyam, "Saliency and ballness driven deep learning framework for cell segmentation in bright field microscopic images", Engineering Applications of Artificial Intelligence 118, 105704, 2023. DOI: https://doi.org/10.1016/j.engappai.2022.105704

Publisher : Elsevier

Year : 2020

Speech Emotion Recognition Using Machine Learning Techniques

Cite this Research Publication : Sasidharan Rajeswari, S., Gopakumar, G., Nair, M. (2021). Speech Emotion Recognition Using Machine Learning Techniques. In: Sharma, H., Saraswat, M., Yadav, A., Kim, J.H., Bansal, J.C. (eds) Congress on Intelligent Systems. CIS 2020. Advances in Intelligent Systems and Computing, vol 1335, pp 169–178, 2020. Springer, Singapore. https://doi.org/10.1007/978-981-33-6984-9_15

Publisher : Springer

Year : 2018

Convolutional neural network‐based malaria diagnosis from focus stack of blood smear images acquired using custom‐built slide scanner

Cite this Research Publication : G Gopakumar, M Swetha, G Sai Siva, GRK Sai Subrahmanyam, "Convolutional neural network‐based malaria diagnosis from focus stack of blood smear images acquired using custom‐built slide scanner," Journal of biophotonics 11 (3), e201700003, 2018.

Publisher : Wiley Online Library

Year : 2017

Microfluidic microscopy-assisted label-free approach for cancer screening: automated microfluidic cytology for cancer screening

Cite this Research Publication : V. Kalyan Jagannadh, Gopakumar G, Subrahmanyam, G. R. K. Sai, and Gorthi, S. Siva, “Microfluidic microscopy-assisted label-free approach for cancer screening: automated microfluidic cytology for cancer screening”, Medical {&} Biological Engineering {&} Computing, vol. 55, pp. 711–718, 2017

Publisher : Medical {&} Biological Engineering {&} Computing,

Year : 2017

Cytopathological image analysis using deep-learning networks in microfluidic microscopy

Cite this Research Publication : Gopakumar G, K, H. Babu, D, M., SS, G., and GR, S. Subrahmany, “Cytopathological image analysis using deep-learning networks in microfluidic microscopy”, Journal of the Optical Society of America A, vol. 34, no. 1, pp. 111-121, 2017

Publisher : Journal of the Optical Society of America A

Year : 2017

Convolutional Neural Network-based malaria Diagnosis from Focus Stack of Blood Smear Images Acquired Using Custom-built Slide Scanner

Cite this Research Publication :
Gopakumar G, Swetha, M., Siva, G. Sai, and Subrahmanyam, G. R. K. Sai, “Convolutional Neural Network-based malaria Diagnosis from Focus Stack of Blood Smear Images Acquired Using Custom-built Slide Scanner”, Journal of Biophotonics, p. e201700003–n/a, 2017

Publisher : Journal of Biophotonics

Year : 2016

Framework for morphometric classification of cells in imaging flow cytometry

Cite this Research Publication : G Gopakumar, VK Jagannadh, SS Gorthi, GRKS Subrahmanyam, "Framework for morphometric classification of cells in imaging flow cytometry", Journal of Microscopy 261 (3), 307-319, 2016, DOI: 10.1111/jmi.12335

Conference Paper

Year : 2023

Copy-Move Forgery Detection Using K-Means and Hu’s Invariant Moments

Cite this Research Publication : N Harshith, D Sindhuja, R Reddy, A Deepthi, G GopaKumar, Copy-Move Forgery Detection Using K-Means and Hu’s Invariant Moments, International Conference on Innovative Computing and Communications, 611-619, 2023

Year : 2022

A Deep Learning Approach to Image Splicing Using Depth Map

Cite this Research Publication : DV Vijay Gopal, G Gopakumar, A Deep Learning Approach to Image Splicing Using Depth Map Advances in Distributed Computing and Machine Learning, 401-411, 2022

Publisher : IEEE Explore

Year : 2022

Face Recognition at varying angles from distant CCTV Footage using Siamese Architecture

Cite this Research Publication : A Stalin, A Sha, AS Kumar, S Nandakumar, G Gopakumar, Face Recognition at varying angles from distant CCTV Footage using Siamese Architecture, 2022 3rd International Conference for Emerging Technology (INCET), 1-6, 2022

Publisher : IEEE Explore

Year : 2022

Face Verification Component for Offline Proctoring System using One-shot learning

Cite this Research Publication : PS Karthik, PNV Chowdary, M Bhargav, G Dhanush, G Gopakumar, Face Verification Component for Offline Proctoring System using One-shot learning, 2022 7th International Conference on Communication and Electronics Systems, 2022

Publisher : IEEE Xplore

Year : 2022

Copy-Move Forgery Detection-A Study and the Survey

Cite this Research Publication : AK Venugopalan, G Gopakumar, Copy-Move Forgery Detection-A Study and the Survey, 2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies, 2022

Publisher : Springer

Year : 2022

A Survey on Image Splice Forgery Detection and Localization Techniques

Cite this Research Publication : Karishma Ram K, G Gopakumar, A Survey on Image Splice Forgery Detection and Localization Techniques, 2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies, 2022

Publisher : Springer

Year : 2021

Enhancement of VerticalThings DSL with Learnable Features

Publisher : Lecture Notes in Electrical Engineeringthis link is disabled, 2021, 735 LNEE, pp. 347–359

Year : 2021

Dynamic Search Paths for Visual Object Tracking

Publisher : Lecture Notes in Electrical Engineeringthis link is disabled, 2021, 736 LNEE, pp. 379–388

Year : 2021

Performance Analysis of Deep Learning Architectures for Super Resolution

Publisher : Journal of Physics: Conference Seriesthis link is disabled, 2021, 1917(1), 012002

Year : 2021

Predicting Covid-19 Positive Cases and Analysis on the Relevance of Features using SHAP (SHapley Additive exPlanation)

Publisher : Proceedings of the 2nd International Conference on Electronics and Sustainable Communication Systems

Year : 2020

An Improved Intrusion Detection System Based on KDD Dataset Using Feature Ranking and Data Sampling

Publisher : Proceedings of the 2020 IEEE International Conference on Communication and Signal Processing, ICCSP 2020, 2020, pp. 1128–1132, 9182060

Year : 2020

Glaucoma Detection from Retinal Fundus Images

Publisher : Proceedings of the 2020 IEEE International Conference on Communication and Signal Processing, ICCSP 2020, 2020, pp. 628–631, 9182388

Year : 2020

Semantic Segmentation of Spectral Images: A Comparative Study using FCN8s and U-NET on RIT-18 Dataset

Publisher : 2020 11th International Conference on Computing, Communication and Networking Technologies, ICCCNT 2020, 2020, 9225461

Year : 2020

Recursive Block Based Keypoint Matching for Copy Move Image Forgery Detection

Publisher : 2020 11th International Conference on Computing, Communication and Networking Technologies, ICCCNT 2020, 2020, 9225658

Year : 2019

An improved random forest algorithm for classification in an imbalanced dataset

Publisher : URSI Asia-Pacific Radio Science Conference, AP-RASC 2019

Year : 2018

Identification of Long Non-coding RNA from inherent features using Machine Learning Techniques

Cite this Research Publication : C. M. Sreeshma, Manu Madhavan, and Gopakumar G., “Identification of Long Non-coding RNA from inherent features using Machine Learning Techniques”, 2018 International Conference on Bioinformatics and Systems Biology (BSB)2018 International Conference on Bioinformatics and Systems Biology (BSB). 2018.

Publisher : 2018 International Conference on Bioinformatics and Systems Biology (BSB)

Conference Proceedings

Year : 2021

Haze Removal Using Generative Adversarial Network

Cite this Research Publication : Amrita Sanjay, J. Jyothisha Nair, G. Gopakumar, Haze Removal Using Generative Adversarial Network, Lecture Notes in Electrical Engineering, 2021.

Publisher : Elsevier

Year : 2021

Breast Mass Classification Using Classic Neural Network Architecture and Support Vector Machine

Cite this Research Publication : R. Priya, V. Sreelekshmi, Jyothisha J. Nair & G. Gopakumar , Breast Mass Classification Using Classic Neural Network Architecture and Support Vector Machine, Lecture Notes in Electrical Engineering,2021

Publisher : Springer

Year : 2017

Improved Transfer Learning through Shallow Network Embedding for Classification of Leukemia Cells

Cite this Research Publication : K. S. Kalmady, Kamath, A. S., Gopakumar G, Subrahmanyam, G. R. K. S., and Gorthi, S. S., “Improved Transfer Learning through Shallow Network Embedding for Classification of Leukemia Cells”, 2017 Ninth International Conference on Advances in Pattern Recognition (ICAPR). IEEE, Bangalore, India, pp. 1-6, 2017

Publisher : 2017 Ninth International Conference on Advances in Pattern Recognition (ICAPR), IEEE

Year : 2016

Automatic Detection of Malaria Infected RBCs from a Focus Stack of Bright Field Microscope Slide Images

Cite this Research Publication : Gopakumar G, Swetha, M., Siva, G. Sai, and Subrahmanyam, G. R. K. S., “Automatic Detection of Malaria Infected RBCs from a Focus Stack of Bright Field Microscope Slide Images”, Proceedings of the Tenth Indian Conference on Computer Vision, Graphics and Image Processing. ACM, New York, NY, USA, 2016

Publisher : Proceedings of the Tenth Indian Conference on Computer Vision, Graphics and Image Processing

Year : 2014

Morphology based Classification of Leukemia Cell lines: K562 and MOLT in a Microfluidics based Imaging Flow Cytometer

Cite this Research Publication :
Gopakumar G, Subrahmanyam, G. R. K. Sai, and Siva, G. Sai, “Morphology based Classification of Leukemia Cell lines: K562 and MOLT in a Microfluidics based Imaging Flow Cytometer”, ICVGIP ’14. ACM, Bangalore, 2014

Publisher : ICVGIP ’14

Book Chapter

Year : 2021

Generating Audio from Lip Movements Visual Input: A Survey

Publisher : Springer, Singapore

Year : 2021

Collision detection for USVs: An analysis on CV algorithms

Cite this Research Publication : Siddharth Kumar, Ram Manoj Potla, Gayathri Ravipati, G. Gopakumar, "Collision Detection for USVs: An Analysis on CV Algorithms", in Smart Computing, 1st Edition, 2021, CRC Press, Pages 12, ISBN 9781003167488

Publisher : CRC Press

Year : 2019

Deep Learning Applications to Cytopathology: A Study on the Detection of Malaria and on the Classification of Leukaemia Cell-Lines

Cite this Research Publication : Gopakumar G and Subrahmanyam, G. R. K. Sai, “Deep Learning Applications to Cytopathology: A Study on the Detection of Malaria and on the Classification of Leukaemia Cell-Lines”, in Handbook of Deep Learning Applications, V. Emilia Balas, Roy, S. Sekhar, Sharma, D., and Samui, P., Eds. Cham: Springer International Publishing, 2019, pp. 219–257.

Publisher : Handbook of Deep Learning Applications, Springer International Publishing

Qualification

Doctorate (2017)
Ph. D. from the Indian Institute of Space Science and Technology in Computer Vision (Medical Image Analysis) under the guidance of Dr. Gorthi R. K. Sai Subrahmanyam. His research thesis is ‘Automatic Feature Extraction and Classification of Cell images for Cytopathology.’

Postgraduate (2011)
M.Tech. in Computer Science with Specialization in Digital Image Computing from the Department of Computer Science, University of Kerala, Karyavattom Campus

Undergraduate (2006)
B.Tech. in Computer Science and Engineering from the College of Engineering, Karunagappally, affiliated to Cochin University of Science and Technology

PhD Students
  • Student Name: Ms Asha S. Benny
    Topic: Deep learning framework for automatic cell segmentation in microscopy images
Invited Talks
Expert Lectures Delivered
Name and Address of the Institution and Name of the Event Event Lecture Topic Date and Time Participants Level (UG/ PG Students, Faculty, Industry Employees, etc.)
Mar Baselios College of Engineering and Technology, Trivandrum Workshop on Soft Computing for Biomedical Applications FDP: Machine Learning Using Tools and Techniques  July 6th, 2017 PG students, Faculty
Saint Gits College of Engineering, Ernakulam One Week FDP on Machine Learning Expert Lecture on Neural Networks and Its applications June 18th – 22nd, 2018 PG students, Faculty, Industry Employees
Indian Institute of Information Technology and Management – Kerala National Level Workshop: Advances in Digital Image Processing and Machine Learning, Bhavishya 2018 FDP: Machine Learning Using Tools and Techniques Oct 27th, 2018 PG students, Faculty, Industry Employees
College of Engineering Karunagappally FDP Machine Learning through Python FDP on Predictive Analysis Jan 25th, 2019 PG students, Faculty
Sree Ayyappa College, Chengannur National Conference : Emerging Technologies in Computer Science Expert Lecture on Neural Networks and Its applications Feb 8th, 2019 PG students, Faculty, Industry Employees
Amrita School of Engineering, Amritapuri National Level Multi Fest: Vidyut 2019 FDP: Machine Learning Using Tools and Techniques March 15th, 2019 UG, PG students
Amrita School of Engineering, Amritapuri National Levele FDP: Deep Learning Unfolded FDP on Predictive Analysis 30th May 2019 PG students, Faculty, Industry Employees
Muthoot Institute of Technology and Science, Ernakulam FDP : Research Trends in Computer Science Expert Lecture on Neural Networks and Its applications July 6th, 2019 PG students, Faculty, Industry Employees
MES College of Engineering, Kuttippuram FDP: Machine Learning Using Tools and Techniques FDP: Machine Learning Using Tools and Techniques July 11th, 2019 PG students, Faculty, Industry Employees
Saint Gits College of Engineering, Ernakulam FDP on Predictive Analysis FDP on Predictive Analysis Oct 11th, 2019 PG students, Faculty, Industry Employees
College of Engineering Perumon Expert Lecture on Neural Networks and Its applications Expert Lecture on Neural Networks and Its applications Nov 13th, 2019 UG Students
Govt Polytechnic Chelakkara Guest Lecture during First Year Induction Program AI & ML Opportunities 16th Jan 2021 Students from Chelakkara Polytechnic
Sreebudha College of Engineering Technical Talk : Mathematics for Machine Learning’ KTU Sponsored FDP  22nd March 2021 PG students, Faculty, Industry Employees
MES Engineering College, Chathannoor Resource person for FDP FDP on Recent Trends in Applying Machine Learning for Mechanical Engineers 28th July 2021 PG students, Faculty, Industry Employees
Mathrubhumi Tech Talk Artificial Intelligence: Opportunities and Challenges Mathrubhumi Live Tech Talk as Part of Opportunities in Education 16th Aug 2021 Live Tech Talk: Open for ALL
Government Engineering College, Manathavady, Vayanad Resource Person for KTU Sponsored FDP Introduction to Optimisation Techniques using Machine Learning Topics 15th Dec 2022 PG students and Faculty Members
Courses Taught
  • Mathematics for Intelligent Systems for B.Tech. CSE AI.
  • Machine Learning and Deep Learning courses for M.Tech. and Research Scholars
  • Pattern Recognition and Computer Vision for B.Tech. CSE students
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