Dr. Rajashree Nayak

Dr. Rajashree Nayak

Assistant Professor, Centre for Data Science

PhD: National Institute of Technology, Rourkela, India

Email: rajashree@jisiasr.org

Linked-in: https://www.linkedin.com/in/rajashree-nayak-ab87b221b/

Google Scholar: https://scholar.google.com/citations?user=idujnrYAAAAJ&hl=en

ORCID ID: https://orcid.org/0000-0002-1303-1979

SCOPUS ID: https://www.scopus.com/authid/detail.uri?authorId=56045389900

Ph.D., Department of Electrical Engineering, National Institute of Technology, Rourkela, India”

Research Topics:

“Super Resolution Image Reconstruction, Biomedical Image Registration, Cyber Image Analysis, Digital Heritage and Skin Lesion Image analysis”.

Research Focus:

I comportment research in  Signal and Image Processing, Super Resolution Image Reconstruction, Pattern Recognition, Artificial Intelligence, Machine Learning, Deep Learning, Cyber Image Analysis, Digital Heritage and Skin Lesion Image analysis. Notable contributions are: Compressive Sensing based Super Resolution Image Reconstruction, P-Spline Interpolation, Molecular Docking based Super Resolution Image Reconstruction, Markov Network based Super Resolution Image Reconstruction, Orthogonal Moment Invariants based Super Resolution Image Reconstruction, Generative Adversarial Network based heritage image Super Resolution, Feature fusion, Similarity in Non-Euclidean space, Novel evolutionary rigid body docking algorithm for multi-modal Image registration, Transfer learning for Melanoma classification in skin lesion images, Deep learning based COVID-19 image classification, Copy-move image forgery localization, Obscene image detection in social media.

Awards & Achievements:

  • Best research paper award at CCSN-2016, India
  • Best research paper award at CCSN-2014, India
  • MHRD Doctoral Scholarship (July 2013- December 2017), MHRD, Govt. of India
  • MHRD Post-Graduate Scholarship (May 2011- June 2013), MHRD, Govt. of India
  • Qualified GATE-2011 in ECE with GATE score: 437, All India Rank: 8262

Journals:

  1. Hansda R., Nayak, R., Balabantaray, B. and Samal, S. 2021. Copy-Move Image Forgery Detection using Phase adaptive Spatio-structured SIFT Algorithm. Journal of SN Computer Science, Springer. DOI: https://doi.org/10.1007/s42979-021-00903-2.
  • Nayak, R., Patra, D. and Balabantaray, B., 2020. Super-Resolution Image Reconstruction Using Molecular Docking. IET Image Processing, 14(12), pp.2922-2936. DOI: https://doi.org/10.1049/iet-ipr.2019.0491. [ IF: 1.98]
  • Nayak, R., Balabantaray, B. and Patra, D., 2020. “A new single image super-resolution using efficient feature fusion and patch similarity in Non-Euclidean space”. Arabian Journal for Science and Engineering, 45(12), pp.10261-10285. DOI: https://doi.org/10.1007/s13369-020-04662-9. [IF: 2.334]
  • Nayak, R. and Patra, D., 2018. Enhanced Iterative Back-Projection Based Super-Resolution Reconstruction of Digital Images. Arabian Journal for Science and Engineering, 43(12), pp 7521–7547. DOI:  https://doi.org/10.1007/s13369-018-3150-1 [IF: 2.334]
  • Nayak, R. and Patra, D., 2018. New single-image super-resolution reconstruction using MRF model”. Neurocomputing, 293, pp.108-129. DOI:  https://doi.org/10.1016/j.neucom.2018.02.090. [IF: 5.719]
  • Nayak, R. and Patra, D., 2017. Super resolution image reconstruction using Penalized-Spline and phase congruency. Computers and Electrical Engineering, 62, pp.232-248. DOI:   https://doi.org/10.1016/j.compeleceng.2016.10.003. [ IF: 3.818]
  • Nayak, R. and Patra, D., 2017. An edge preserving IBP based super resolution image reconstruction using P-spline and MuCSO-QPSO algorithm. Microsystem Technologies, 23(3), pp.553-569. DOI:  https://doi.org/10.1007/s00542-016-2972-6. [IF: 1.737]
  • Panda, R., Agrawal, S., Sahoo, M. and Nayak, R., 2017. A novel evolutionary rigid body docking algorithm for medical image registration. Swarm and Evolutionary Computation, 33, pp.108-118. DOI:  https://doi.org/10.1016/\\j.swevo.2016.11.002. [IF: 7.177]
  • Nayak, R. and Patra, D., 2016. Super resolution image reconstruction using weighted combined pseudo-Zernike moment invariants. AEU-International Journal of Electronics and Communications, 70(11), pp.1496-1505. DOI:  https://doi.org/10.1016/j.aeue.2016.09.001. [IF: 3.183]

Book Chapters:

  • Nayak, R. and Balabantaray, B. Generative Adversarial Network for Heritage Image Super Resolution, Book: Computer Vision and Image Processing, Springer Singapore, CCIS 1377, pp. 1-13, December 4-6, 2021. eBook ISBN: 978-981-16-1086-8.
  • Hansda, R.,  Nayak, R. and Balabantaray, B. Copy-Move Image Forgery Detection Using Spatio-Structured SIFT Algorithm, Book: Computer Vision and Image Processing, Springer Singapore, CCIS 1376, pp. 1-12, December 4-6, 2021. eBook ISBN: 978-981-16-1086-8.
  • Nayak, R. and Balabantaray, B.K. MoBMGAN: Modified GAN based Transfer learning for automatic detection of COVID-19 cases using Chest X-ray Images, Book: Computational Modelling and data Analysis in COVID-19 Research, CRC Press, pp.29-46, May 10, 2021. ISBN: 9780367680367.
  • Nayak, R., Krishna, L.V. and Patra, D. Enhanced Super-Resolution Image Reconstruction Using MRF Model, Progress in Intelligent Computing Techniques: Theory, Practice, and Applications. Springer, Singapore, 2018, pp.207-215. eBook ISBN: 978-981-10-3376-6.

Conferences:

  1. Hansda, R., Nayak, R. and Balabantaray, B. Copy-Move Image Forgery Detection via Combined Pseudo-Zernike Moment Invariants, 3rd International Conference on Energy, Power and Environment: Towards Clean Energy Technologies, NIT Meghalaya, IEEE, 2021.
  • Hansda, R., Nayak, R. and Balabantaray, B. Copy-Move Image Forgery Detection using Spatio-structured SIFT Algorithm, 5th IAPR International Conference on Computer Vision and Image Processing, IIIT Allahabad, 4-6 December 2020.
  • Nayak, R. and Balabantaray, B. Generative Adversarial Network for Heritage Image Super Resolution, 5th IAPR International Conference on Computer Vision and Image Processing, IIIT Allahabad, 4-6 December 2020.
  • Balabanataray, B. K., Chakravarty, R.,  Panda, A. K.  and Nayak, R. Melanoma Classification Through Transfer Learning by the Analysis of Skin Lesion Images, 3rd International Conference On Computing and Communication Systems (I3CS 2020), NEHU Shillong.
  • Nayak, R., Patra, D.  Development of efficient methods for image super-resolution image reconstruction, ICVGIP, Doctoral Symposium, IIT Guwahati, 18-22 December, 2016.
  • Nayak, R. and Patra, D.  Learning-based single image super resolution using MRF model, CCSN, 2016, Kolkata, 24-25 December 2016.
  • Nayak, R. and Patra, D. Image interpolation using adaptive P-spline, 2015 Annual IEEE India Conference (INDICON), New Delhi, 2015, pp. 1-6.
  • Nayak, R., Patra D. and Harshavardhan, S. Sparse representation based image super resolution reconstruction, TENCON 2015 – 2015 IEEE Region 10 Conference, Macao, 2015, pp. 1-6.
  • Nayak, R.,  Harshavardhan, S.  and Patra, D.  Morphology based iterative back-projection for super-resolution reconstruction of image, 2014 2nd International Conference on Emerging Technology Trends in Electronics, Communication and Networking, Surat, 2014, pp. 1-6.
  1. Nayak, R., Monalisa S., and Patra, D.  Spatial super resolution based image reconstruction using HIBP, 2013 Annual IEEE India Conference (INDICON), Mumbai, 2013, pp. 1-6.