- Deep Learning,
- Machine Learning
| Degree | Organization/Institution | Specialization | Year of Passing |
| Ph.D.(pursuing) | SRM University, Chennai | Deep Learning for Healthcare informatics | Pursuing |
| M.Tech | SRKR Engg.College,Bhimavaram | CST | 2012 |
| B.Tech | SVECW,Bhimavaram | CSE | 2010 |
Publications in National/International Conferences:
- P. R. Budumuru, A. R. Shaik, B. V. V. Satyanarayana, S. P. Manikanta, K. S. Sharmila and D. Durga Prasad, “Normalized Algorithm with Image Processing Methods for Estimation of Crack Length,” 2022 6th International Conference on Electronics, Communication and Aerospace Technology, Coimbatore, India, 2022, pp. 1436-1439, doi: 10.1109/ICECA55336.2022.10009306.
- K. S. Sharmila, S. Thanga Revathi and P. K. Sree, “Convolution Neural Networks based lungs disease detection and Severity classification,” 2023 International Conference on Computer Communication and Informatics (ICCCI), Coimbatore, India, 2023, pp. 1-9, doi: 10.1109/ICCCI56745.2023.10128188.
- Sharmila, K. Soni, and Pokkuluri Kiran Sree. “Drug-Drug Interaction: An Improved Prediction Approach Based on Convolutional Neural Networks.” 2023 International Conference on Sustainable Communication Networks and Application (ICSCNA). IEEE, 2023.
Journal Publications:
- Raman, R., Mewada, B., Meenakshi, R., Jayaseelan, G. M., Sharmila, K. S., Taqui, S. N., … Iqbal, A. (2024). Forecasting the PV Power Utilizing a Combined Convolutional Neural Network and Long Short-Term Memory Model. Electric Power Components and Systems, 52(2), 233–249. https://doi.org/10.1080/15325008.2023.2217193
- Sharmila, K.S., Asha, A.V.S., Archana, P., Chandra, K.R. (2023). Single Image Dehazing Through Feed Forward Artificial Neural Network. In: Gupta, N., Pareek, P., Reis, M. (eds) Cognitive Computing and Cyber Physical Systems. IC4S 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 472. Springer, Cham. https://doi.org/10.1007/978-3-031-28975-0_9
- Soni Sharmila, K., Manikanta, S.P., Santosh Kumar Patra, P., Satyanarayana, K., Ramesh Chandra, K. (2024). An Efficient Denoising of Medical Images Through Convolutional Neural Network. In: Pareek, P., Gupta, N., Reis, M.J.C.S. (eds) Cognitive Computing and Cyber Physical Systems. IC4S 2023. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 536. Springer, Cham. https://doi.org/10.1007/978-3-031-48888-7_39
- COMPUTER GRAPHICS
Publisher: Notion Press
- “Paper scanning machine based on internet of things” patent no. 367333-001.
- Research Methodology
- Python for data science
- Introduction to Operating Systems
- Deep learning
- Introduction to Machine Learning
- Medical image Analysis
- The joy of computing using python
- Roadmap for patents creation
- Citizen Data Science using Python Certification by Infosys spring board
- Faculty Enablement Program on Generative AI series by infosis spring board
- Nptel online certification on “joy of computing using python”
- Societal Applications of Machine Learning
- Recent Trends in Artificial Intelligence and Cyber Security
- The joy of computing using python
- Deep learning
- Introduction to Machine Learning
- Medical image Analysis
- Roadmap for patents creation
- Project coordinator
- Counsellor and mentor
- Project Guide
- UG Level:
Python programming, Computer Networks, Database Management System, Computer Graphics, Computer organization, Full Stack Development, Software project Management, web technology, Design and analysis of algorithms, operating systems - PG Level:
Operating systems, Full Stack Development, Software Requirements and estimation.
The recent publications and research contributions can be viewed from the following URLs:
| Profile | Link |
| Google Scholar | http://scholar.google.co.in/citations?user=kh3zl-sAAAAJ |
| Vidwan | 373469 |
| Research Gate | http://www.researcherid.com/rid/HLP-4102-2023 |
| ORCID | http://www.orcid.org/0000-0002-7386-0963 |
| Scopus | http://www.scopus.com/authid/detail.url?authorId=58092723600 |
