Pratikshya Sharma

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Dr Pratikshya Sharma PhD,M.Tech,B.Tech

Lecturer


Summary

Her research interest lies in "application of artificial intelligence and Machine Learning techniques in computer vision to solve real world problems".

About

Pratikshya is a permanent academic staff at Sheffield Hallam University. She was awarded Vice-Chancellor's Research Scholarships in 2018 to pursue her PhD in the UK. She has a PhD (Computer Vision and Applied AI and Machine Learning) and a master’s degree in (Computer Science and Engineering). Broadly, her research focuses on application of artificial intelligence and Machine Learning techniques in computer vision to solve real world problems. She also has research interest in face analysis, facial expression analysis, estimating emotions from human face by examining micro/macro expressions employing deep learning and machine learning concepts. She has keen interest and experience in building models for improving the image quality using deep learning based super resolution algorithms. Additionally, her interest lies in exploring generative models and their architecture to reconstruct and regain the facial attributes to enable expression as well as various other kinds of facial analysis. She is an active researcher with more than 10 scientific publications. She also has over 8 years of teaching experience in the UK and abroad.

Her research publications include:

1. Sharma, P., Coleman, S., Yogarajah, P. et al. Comparative analysis of super-resolution reconstructed images for micro-expression recognition. Adv. in Comp. Int. 2, 24 (2022).

https://doi.org/10.1007/s43674-022-00035-x

2. Sharma, P.; Coleman, S.; Yogarajah, P.; Taggart, L. and Samarasinghe, P. (2022). Evaluation of Generative Adversarial Network Generated Super Resolution Images for Micro Expression Recognition. In Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods, ISBN 978-989-758-549-4, ISSN 2184-4313, Feb,2022, pages 560-569.

3. P. Sharma, S. Coleman, P. Yogarajah, L. Taggart and P. Samarasinghe, "Magnifying Spontaneous Facial Micro Expressions for Improved Recognition," 2020 25th International Conference on Pattern Recognition (ICPR), 2021, pp. 7930-7936, doi: 10.1109/ICPR48806.2021.9412585.

4. Sharma, P., Coleman, S., Yogarajah, P. & Laurence, T. (2019). Micro expression classification accuracy assessment. IMVIP 2019: Irish Machine Vision & Image Processing, Technological University Dublin, Dublin, Ireland, August 28-30. doi:10.21427/kbny-0a41

5. Accurate Drainage Network Extraction from Satellite Imagery—A Survey, Advances in Communication, Cloud, and Big Data. Lecture Notes in Networks and Systems, vol 31. Springer, Singapore. https://doi.org/10.1007/978-981-10-8911-4_16

6. An analysis of the Intelligent Predictive String Search Algorithm: A Probabilistic Approach, I.J. Information Technology and Computer Science, 2017, 2, 66-75 Published Online February 2017 in MECS (https://www.mecs-press.org/) DOI: 10.5815/ijitcs.2017.02.08

7. S. Choudhury, M. P. Pradhan, P. Sharma and S. K. Kar, "Determining Urban Emotion using an unsupervised learning approach: A case study around Majitar, East District, Sikkim," 2016 International Conference on Energy Efficient Technologies for Sustainability (ICEETS), 2016, pp. 134-141, doi: 10.1109/ICEETS.2016.7582913.

8. Determining Urban Emotion using a Supervised Learning Approach: A Case Study around Majitar, East, International Journal of Computer Applications (0975 – 8887) Volume 144 –No.5, pp 37-44, June 2016.

Teaching

School of Computing and Digital Technologies

College of Business, Technology and Engineering

Subject area:

  • Computing (Software Engineering)

Courses taught:

  • BSc Software engineering
  • BSc Computer Science
  • BSc Computer Science with AI

Modules taught:

  • Robotics
  • Artificial Intelligence
  • Computer Architecture
  • Robotics with Artificial Intelligence

Publications

Journal articles

Sharma, P., Coleman, S., Yogarajah, P., Taggart, L., & Samarasinghe, P. (2022). Comparative analysis of super-resolution reconstructed images for micro-expression recognition. Advances in Computational Intelligence, 2 (3). http://doi.org/10.1007/s43674-022-00035-x

Gurung, D., Chakraborty, U.K., & Sharma, P. (2017). An analysis of the Intelligent Predictive String Search Algorithm: A Probabilistic Approach. International Journal of Information Technology and Computer Science, 9 (2), 66-75. http://doi.org/10.5815/ijitcs.2017.02.08

Gurung, D., Chakraborty, U.K., & Sharma, P. (2016). Intelligent Predictive String Search Algorithm. Procedia Computer Science, 79, 161-169. http://doi.org/10.1016/j.procs.2016.03.116

Choudhury, S., P., M., Sharma, P., & K., S. (n.d.). Determining Urban Emotion using a Supervised Learning Approach: A Case Study around Majitar, East. International Journal of Computer Applications, 144 (5), 37-44. http://doi.org/10.5120/ijca2016910291

Khatun, F., & Sharma, P. (n.d.). Arbitrary Polygon Query Handling Algorithm on GIS based on three Value Logic- An Approach. International Journal of Computer Applications, 144 (1), 32-35. http://doi.org/10.5120/ijca2016910090

Conference papers

Sharma, P., Coleman, S., Yogarajah, P., Taggart, L., & Samarasinghe, P. (2022). Evaluation of Generative Adversarial Network Generated Super Resolution Images for Micro Expression Recognition. Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods, 560-569. http://doi.org/10.5220/0010820100003122

Sharma, P., Coleman, S., Yogarajah, P., Taggart, L., & Samarasinghe, P. (2021). Magnifying Spontaneous Facial Micro Expressions for Improved Recognition. 2020 25th International Conference on Pattern Recognition (ICPR), 7930-7936. http://doi.org/10.1109/icpr48806.2021.9412585

Khatun, F., & Sharma, P. (2018). Strahler Order Classification and Analysis of Drainage Network by Satellite Image Processing. In Lecture Notes in Electrical Engineering, (pp. 915-922). Springer Singapore: http://doi.org/10.1007/978-981-10-7901-6_98

Khatun, F., & Sharma, P. (2018). Strahler Order Classification and Analysis of Drainage Network by Satellite Image Processing. In Lecture Notes in Electrical Engineering, (pp. 915-922). Springer Singapore: http://doi.org/10.1007/978-981-10-7901-6_98

Choudhury, S., Pradhan, M.P., Sharma, P., & Kar, S.K. (2016). Determining Urban Emotion using an unsupervised learning approach: A case study around Majitar, East District, Sikkim. 2016 International Conference on Energy Efficient Technologies for Sustainability (ICEETS), 134-141. http://doi.org/10.1109/iceets.2016.7582913

Sharma, P. Accurate Drainage Network Extraction from Satellite Imagery—A Survey. In Advances in Communication, Cloud, and Big Data, (pp. 978-981). Springer: https://doi.org/10.1007/978-981-10-8911-4_16

Sharma, P. Accurate Drainage Network Extraction from Satellite Imagery—A Survey. In Advances in Communication, Cloud, and Big Data, (pp. 978-981). Springer: https://doi.org/10.1007/978-981-10-8911-4_16

Sharma, P. Micro expression classification accuracy assessment. In Irish Machine Vision & Image Processing. http://doi.org10.21427/kbny-0a41

Sharma, P. String Searching Algorithm: A Predictive Approach. In International Conference on Communication Computing and Virtualization. https://www.ijais.org/proceedings/icccv2016/number2/920-1664

Sharma, P. String Searching Algorithm: A Predictive Approach. In International Conference on Communication Computing and Virtualization. https://www.ijais.org/proceedings/icccv2016/number2/920-1664

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