Domain of interest:
Domain of interest:
Medical Image Processing, Deep learning, Generative Adversarial Networks, Machine learning.
Medical Image Processing, Deep learning, Generative Adversarial Networks, Machine learning.
Roles and Responsibilities:
Teaching undergraduate students @MIT, Manipal.
Lab courses related to networking and Embedded Systems.
Guided 02 undergraduate major projects.
Collaborate with eminent Professors for research activities.
Coordinate events like workshops, and hackathons @MIT, Manipal.
Other interests:
Pencil sketching, singing, traveling.
LATEST WORKS:
1) IAPR Newsletter published - October 2021 ISSUE
2) Resource person for handson - session at NITK Surathkal "FDP on satellite image processing using deep learning" (March 2022)
3) Assisting project works of 01 PhD student and 01 Mtech research student (at NITK - research group guided by Dr. Jidesh P.)
4) Handling Computer network protocols and Microprocessor lab at MIT, Manipal for 4 sem B. Tech students.
5) Defended PhD thesis on May 5 2022.
6) Received IEEE Best thesis Award in Ph D Forum - WINTECHCON 2022 (https://wintechcon.com/index.html#Awards)
Journals:
1) Rao, S., Smitha, A., & Kulkarni, K. (2018). Smart Phone based Cost Effective Visitor Management System for Smart Offices. International Journal of Interactive Mobile Technologies (iJIM), 12(6), 112. doi:10.3991/ijim.v12i6.9476.
2) Smitha, A., & Jidesh, P. (2021). A nonlocal deep image prior model to restore optical coherence tomographic images from gamma distributed speckle noise. Journal of Modern Optics, 68(18), 1002–1017. doi:10.1080/09500340.2021.1968052.1.464 Impact Factor, Q2, Scopus, SCI, H-index 91, Q3
3) A. Smitha, I.P. Febin, P. Jidesh, (2022). A retinex based non-local total generalized variation framework for OCT image restoration, Biomedical Signal Processing and Control, Volume 71, Part B, 103234, ISSN 1746-8094, https://doi.org/10.1016/j.bspc.2021.103234. (https://www.sciencedirect.com/science/article/pii/S1746809421008314) 3.88 Impact factor, SCI, Scopus, H-index 72, Q2.
4) Smitha, A., Jidesh, P. (2022) Classification of Multiple Retinal Disorders from Enhanced Fundus Images Using Semi-supervised GAN. SN COMPUT. SCI. 3, 59. https://doi.org/10.1007/s42979-021-00945-6.
5) Smitha A., Jidesh P. (2022) Detection of retinal disorders from OCT images using Generative Adversarial Networks, Mutimedia Tools and Applications, https://doi.org/10.1007/s11042-022-12475-1, 2.757 Impact factor, SCIE, Scopus, H-index 70, Q1.
6) Shastry, A., Smitha, A., George, S., & Jidesh, P. (2022). Restoration and enhancement of aerial and synthetic aperture radar images using generative deep image prior architecture. PFG–Journal of photogrammetry, remote sensing and geoinformation science, 90(6), 497-529.
Conferences:
1) A. Smitha, M. M. Manohara Pai, N. Ajam and J. Mouzna, "An optimized adaptive algorithm for authentication of safety critical messages in VANET," 2013 8th International Conference on Communications and Networking in China (CHINACOM), 2013, pp. 149-154, doi: 10.1109/ChinaCom.2013.6694582.
2) S. Mallissery, M. M. M. Pai, A. Smitha, R. M. Pai and J. Mouzna, "Improvizmg the public key infrastructure to build trust architecture for VANET by using short-time certificate management and Merkle Signature Scheme," 2014 Asia-Pacific Conference on Computer Aided System Engineering (APCASE), 2014, pp. 146-151, doi: 10.1109/APCASE.2014.6924489.
3) S. Mallissery, M. M. Manohara Pai, R. M. Pai and A. Smitha, "Cloud enabled secure communication in Vehicular Ad-hoc Networks," 2014 International Conference on Connected Vehicles and Expo (ICCVE), 2014, pp. 596-601, doi: 10.1109/ICCVE.2014.7297617.
4) Smitha A., Jidesh P., Febin I.P. (2020) Retinal Vessel Classification Using the Non-local Retinex Method. In: Tiwary U., Chaudhury S. (eds) Intelligent Human Computer Interaction. IHCI 2019. Lecture Notes in Computer Science, vol 11886. Springer, Cham. https://doi.org/10.1007/978-3-030-44689-5_15.
5)Smitha A., Jidesh P. (2021) A Semi-supervised Generative Adversarial Network for Retinal Analysis from Fundus Images. In: Singh S.K., Roy P., Raman B., Nagabhushan P. (eds) Computer Vision and Image Processing. CVIP 2020. Communications in Computer and Information Science, vol 1376. Springer, Singapore. https://doi.org/10.1007/978-981-16-1086-8_31.
6)Smitha, A., Jidesh, P., Balaji, J. J., & Lakshminarayanan, V. (2021, August). Development and validation of a novel automated method for quantification of choroidal thickness in age-related macular degeneration. In Applications of Digital Image Processing XLIV (Vol. 11842, p. 118422E). International Society for Optics and Photonics.
7) Abhinaba Hazarika, Jidesh P., Smitha A. (2022) Comparative analysis of machine learning and deep learning models for ship classification from satellite images, presented in CVIP 2021, Allahabad.
8) Tikle, S., Jidesh, P., & Smitha, A. (2023). Assessing Damage of Natural Disasters from Satellite Imagery Using a Deep Learning Model. In Advances in Signal Processing, Embedded Systems and IoT: Proceedings of Seventh ICMEET-2022 (pp. 509-518). Singapore: Springer Nature Singapore.