Dr. Megha Chhabra

About

Dr. Megha Chhabra is currently working as an Associate Professor in the Department of Computer Science & Engineering in School of Engineering & Technology, Sharda University. She has completed her M.Tech from Thapar University. She is a Ph.D. in Image Forensics. She has published multiple papers in journals and conferences which focus on Image processing.

Programme Coordinator for M-TECH Computer Science & Engineering

Experience

• 13 years

Qualification

• PhD-Image forensics-Pursuing 
• M.Tech-CSA-Thapar University 2012
• MSc-CS - DAV Jalandhar-2010- University Gold medalist

Award & Recognition

• MSc-Gold medal-University First Position. 
• University Scholarship in M.Tech 
• A reviewer of various SCI/SCOPUS Indexed journals and IEEE conferences. 

Research

Journals: 

• “State-of-the-Art: A Systematic Literature Review of Image Segmentation in Latent Fingerprint Forensics”, Recent patents in computer science, (2020) ISSN: 2666-2566, DOI: 10.2174/2213275912666190429153952. (In press)
• “Boosting the Classification Performance of Latent Fingerprint Segmentation using Cascade of Classifiers”, Intelligent Decision Technologies, (2020), ISSN:  (In press).
• “Prediction and Judgmental Adjustments of Supply-Chain Planning in Festive Season. Global Journal of Computer Science and Technology, (2018). ISSN 0975-4172.
• “Case Study: Analysis and Predictions of Shipment Load in Festive Season.” , International Journal of Advanced Research in Computer Science and Software Engineering7(7) ISSN(E): 2277-128X, ISSN(P): 2277-6451, pp. 491-49, (2017).
• “ROI Reduction Approach for Fast Circle Recognition using Classical Hough Transform”, International Journal of Advanced Research in Computer Science and Software Engineering, ISSN: 2277 128X, Vol.6, Issue 6, June, (2016).
• “An Improved Automatic Brain Tumor Detection System”, International Journal of Advanced Research in Computer Science and Software Engineering, ISSN: 2277 128X, Vol.5, Issue 4, (2014).
• “Monitoring and Controlling Systems Behavior to Achieve Optimal Reliability using Fuzzy Cognitive Maps”, International Journal of Advanced Research in Computer Science and Software Engineering, ISSN: 2277 128X, Vol.5, Issue 5, (2014).
• "Accurate Corner Detection Methods using Two Step Approach", Global Journal of Computer Science and Technology (GJCST), (2011), Online ISSN: 0975-4172, Print ISSN: 0975-4350.

Conferences:

• “Bagging and Boosting based Latent Fingerprint Image Classification and Segmentation”, 3rd international conference on innovative computing and communication (icicc-2020-springer).
• “State-of-the-art: Feature Extraction and Feature Selection in Latent Fingerprint Segmentation”, 2nd International Conference on Recent Multidisciplinary Research (ICRMR-2018) at Thailand during 23-24 November, 2018.
• “Latent Fingerprint Forensics - A Survey” is published as a paper in INDIACOM – 02nd -03rd March2017; International Conference, IEEE Delhi Section at Bharati Vidyapeeth, New Delhi (INDIA).
• “Improved Hough Transform for Fast Iris Detection”, IEEE International Conference on Signal Processing Systems, Dalian, China on 5-7 July, 2010.

Book Chapter:

• “Accurate and Robust Iris Recognition Using Modified Classical Hough Transform.” In: Mishra D., Nayak M., Joshi A. (eds) Information and Communication Technology for Sustainable Development. Lecture Notes in Networks and Systems, vol 10. Springer, Singapore, (2018).

Publication

• “Intelligent waste classification approach based on improved multi-layered convolutional neural network”, Multimed Tools Appl (2024). https://doi.org/10.1007/s11042-024-18939-w (2024-SCI)
• “Patch-Based Breast Cancer Histopathological Image Classification using Deep Learning”, International Journal of Performability Engineering 19, no. 9 (2023): 60. (2023-SCOPUS).
• “A Fuzzy Cognitive Map of the Quality of User Experience Determinants in Mobile Application Design” Journal of Intelligent & Fuzzy Systems, 44(2), 2957-2979, DOI:10.3233/JIFS-222111, IOS Press. (2023-SCI).
• “Improving automated latent fingerprint detection and segmentation using deep convolutional neural network” Neural Computing and Applications, https://doi.org/10.1007/s00521-022-07894- y(0123456789().,-volV) (2023-SCI).
• “Boosting the Classification Performance of Latent Fingerprint Segmentation using Cascade of Classifiers”, Intelligent Decision Technologies, 2021 : 1 – 13. (2021-SCI)

Certifications

• Undergone one-month training in “Scrum Framework” from RAGASOFT SOLUTIONS PVT LTD as a Trainee Scrum Master.
• Online course Certificates: Machine learning, Inferential statistics, fundamentals of Python, Deep Learning etc. 

Area of Interest

• Deep learning
• Pattern recognition
• Graph Analysis
• Machine learning
• Image forensics