Dr. Chiranjeevi Manike

Papers Published

1. Sreedevi, Alampally, and Chiranjeevi Manike. “A smart solution for tomato leaf disease classification by modified recurrent neural network with severity computation.” Cybernetics and Systems2 (2024): 409-449.
2. Sreedevi, Alampally, and Chiranjeevi Manike. “Development of weighted ensemble transfer learning for tomato leaf disease classification solving low resolution problems.” The Imaging Science Journal2 (2023): 161-187.
3. Sreedevi, Alampally, and Chiranjeevi Manike. “TOMATO LEAF DISEASE DETECTION USING CUTTING-EDGE DEEP LEARNING ARCHITECTURES.”  For. Res66.1 (2023): 4320-4332.
4. Kulkarni, Girish, and Chiranjeevi Manike. “Heuristic-Based Ensemble Model Selection Strategy with Parameter Tuning for Optimal Diabetes Mellitus Prediction.” International Journal of Image and Graphics(2023): 2450046.
5. Venkateswarulu, N., Chiranjeevi Manike, and O. Obulesu. “An Industry Framework for Remote Health Monitoring using Machine Learning Models to Predict a Disease.” (2023).
6. Manike, Chiranjeevi, Ashok Kumar Nanda, and Tejashwini Gajulagudem. “Hadoop Scalability and Performance Testing in Homogeneous Clusters.” Proceedings of ICETIT 2019: Emerging Trends in Information Technology. Cham: Springer International Publishing, 2019. 907-917.
7. Manike, Chiranjeevi, and Hari Om. “Sliding-window based method to discover high utility patterns from data streams.” Computational Intelligence in Data Mining-Volume 3: Proceedings of the International Conference on CIDM, 20-21 December 2014. Springer India, 2015.
8. Manike, Chiranjeevi, and Hari Om. “Modified GUIDE (LM) algorithm for mining maximal high utility patterns from data streams.” International Journal of Computational Intelligence Systems3 (2015): 517-529.
9. Manike, Chiranjeevi, and Hari Om. “Time-Efficient Tree-Based Algorithm for Mining High Utility Patterns.” Advances in Intelligent Informatics. Cham: Springer International Publishing, 2015. 409-418.

Subjects Taught

1. Data Science
2. Big Data Analytics
3. Machine Learning
4. Deep Learning
5. Data Warehousing and Data Mining
6. Database Management Systems
7. Information Retrieval Systems
8. Ethical Hacking
9. Natural Language Processing
10. Neural Networks
11. Soft Computing
12. Block Chain Technologies
13. Python Full-Stack Development

Books Published

1. Issac, Biju, and Nauman Israr, eds. Case studies in intelligent computing: achievements and trends. CRC Press, 2014.