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Our Publications

  • CAIR

Engineering Intelligence for The Real World

At CAIR, we’re building a vibrant research community committed to solving real-world problems with intelligent technologies. Our focus spans Edge AI, High-Performance Computing (HPC), Data Science, and Cloud Computing — powering innovation that’s fast, reliable, and future-ready. With strong partnerships across industry and academia, CAIR is where fundamental research transforms into applied breakthroughs.
Engineering Intelligence
  • ​​HPC PUBLICATIONS

Where Data Meets Speed

  • Bidari, Indira, and Satyadhyan Chickerur.
  • Deep recurrent residual U-Net with semi-supervised learning for deforestation change detection. SN Computer Science, 5(7), 2024: 893.
  • Konnurmath, Guruprasad, and Satyadhyan Chickerur.
  • Real-time frame rate controlled dynamic voltage and frequency scaling for GPU power consumption optimization. AIP Conference Proceedings, 3131(1), AIP Publishing, 2024.
  • Jadhav, Varsha S., Rajesh Yakkundimath, and Guruprasad Konnurmath.
  • Cervical cancer severity characterization using machine learning techniques. Indian Journal of Gynecologic Oncology, 22(4), 2024: 1–10.
  • Badiger, Ramesh M., Rajesh Yakkundimath, Guruprasad Konnurmath, and Praveen M. Dhulavvagol.
  • Deep learning approaches for age-based gesture classification in South Indian Sign Language. Engineering, Technology & Applied Science Research, 14(2), 2024: 13255–13260.
  • Kampli, Gurunath, Satyadhyan Chickerur, and Manjoykumar Chitawadagi.
  • IoT system implementation for real-time concrete strength prediction: Experimental design, variance evaluation, cost analysis, and implementation ease. Innovative Infrastructure Solutions, 9(7), 2024: 260.
  • DATA SCIENCE PUBLICATIONS

Smarter Data, Better Lives

  • Koluragi, P., Deshpande, Y., Dhumale, G., Chikkamath, S., Nirmala, S.R., & Budihal, S.V.
  • Multi-model approach for Alzheimer disease detection and classification. 2024 3rd International Conference for Innovation in Technology (INOCON), Bangalore, India, 2024, pp. 1–5. doi: 10.1109/INOCON60754.2024.10511750
  • Shidramshettar, R., Bonageri, A., Kumbargeri, V., Chikkamath, S., Nirmala, S.R., & Budihal, S.
  • Enhanced retinal vessel segmentation using U-Net framework. 2024 IEEE International Conference on Contemporary Computing and Communications (InC4), Bangalore, India, 2024, pp. 1–5. doi: 10.1109/InC460750.2024.10649089
  • Medhi, J.P., Nirmala, S.R., Choudhury, S., & Dandapat, S.
  • Improved detection and analysis of macular edema using modified guided image filtering with modified level set spatial fuzzy clustering on optical coherence tomography images. Biomedical Signal Processing and Control, 79(2), 2023: 1041–1049. (Q1)
  • Kaushik, P., & Nirmala, S.R.
  • Automated system for detection and classification of cystoid macular oedema using OCT images. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 2023: 1–15. (Q2) https://doi.org/10.1080/21681163.2023.2237606
  • Saikia, S.J., & Nirmala, S.R.
  • Identification of disease genes and assessment of eye-related diseases caused by disease genes using JMFC and GDLNN.Computer Methods in Biomechanics and Biomedical Engineering, 25(4), 2022: 359–370.
  • Mazumdar, J.B., & Nirmala, S.R.
  • Deep learning framework for biometric authentication using retinal images. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 11(3), 2022: 740–749. (Q1)
  • Sandilya, M., & Nirmala, S.R.
  • Compressed sensing MRI reconstruction using convolutional dictionary learning and Laplacian prior. In Senjyu, T., et al. (Eds.), IOT with Smart Systems, Smart Innovation, Systems and Technologies, vol. 251. Springer, Singapore, 2022. https://doi.org/10.1007/978-981-16-3945-6_65
  • Kanakaraddi, S.G., Chikaraddi, A.K., Aivalli, N., Maniyar, J., & Singh, N.
  • Sentiment analysis of COVID-19 tweets using machine learning and natural language processing. Advances in Intelligent Systems and Computing, vol. 1415. Springer, Singapore, 2022. https://doi.org/10.1007/978-981-16-7330-6_28
  • Gull, K., Kanakaraddi, S., & Chikaraddi, A.
  • COVID-19 outbreak prediction using additive time series forecasting model. Trends in Sciences, 19(22), 2022: 1919.
  • Desai, S.D.
  • Desai, S., et al.
  • Low-dose imaging: Prediction of projections in sinogram space. In Smys, S., et al. (Eds.), Computational Vision and Bio-Inspired Computing, Advances in Intelligent Systems and Computing, vol. 1318. Springer, Singapore, 2021. https://doi.org/10.1007/978-981-33-6862-0_43
  • Desai, S., et al.
  • Desai, S., et al.
  • Breast cancer detection using GAN for limited labeled dataset. 2020 12th International Conference on Computational Intelligence and Communication Networks (CICN), Bhimtal, India, 2020, pp. 34–39. doi: 10.1109/CICN49253.2020.9242551
  • Ballari, G., Giraddi, S., Chickerur, S., & Kanakaraddi, S.
  • An explainable AI-based skin disease detection. In ICT Infrastructure and Computing: Proceedings of ICT4SD 2022, pp. 287–295. Springer Nature Singapore.
  • Patil, S.S., Patil, M.S., Chickerur, S., Giraddi, S., Shahapur, S.N., & Hadalageri.
  • Distributed deep learning with data parallelism for diabetic retinopathy classification. In Smart Trends in Computing and Communications, 2023, pp. 49–60. Springer Nature Singapore.
  • Giraddi, V., Giraddi, S., Kanakaraddi, S., & Patil, M.
  • Assessment of lung cancer histology using EfficientNet. In Mobile Computing and Sustainable Informatics: Proceedings of ICMCSI 2023, pp. 395–403. Springer Nature Singapore.
  • Sulibhavi, P.H., Kanakaraddi, S.G., & Giraddi, S.
  • A study on kidney segmentation techniques using DNN models. In Smart Computing and Communication, 2023, pp. 839–849. Springer Nature Singapore.
  • Giraddi, S., Mugdha, S., Kanakaraddi, S., & Chickerur, S.
  • Glaucoma diagnosis: Handcrafted features versus deep learning. In Mobile Computing and Sustainable Informatics: Proceedings of ICMCSI 2022, pp. 869–881. Springer Nature Singapore.
  • Patil, S.A., Patil, M.S., Giraddi, S., Chickerur, S., Boormane, V.M., & Gamanagatti, G.
  • Pipeline parallelism in distributed deep learning for diabetic retinopathy classification. Procedia Computer Science, 215, 2022: 393–402.
  • Jalannavar, A., Kanakaraddi, S.G., & Handur, V.S.
  • Migraine prediction using deep learning model. 2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT), Mandya, India, 2022, pp. 1–8. doi: 10.1109/ICERECT56837.2022.10059843
  • Korti, S., & Kanakaraddi, S.G.
  • Depression detection from Twitter posts using NLP and machine learning techniques. 2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT), Mandya, India, 2022, pp. 1–6. doi: 10.1109/ICERECT56837.2022.10059773
  • Sulibhavi, P.H., & Kanakaraddi, S.G.
  • A study on kidney segmentation techniques using DNN models. Lecture Notes in Networks and Systems, 650, 2023: 839–849.
  • CLOUD COMPUTING PUBLICATIONS

Intelligence in the Cloud

  • Vishesha, M., et al.
  • Optimized placement of service function chains in edge cloud using LSTM. SN Computer Science, 2024. (Accepted)
  • Narayan, G., et al.
  • A framework for data provenance assurance in cloud environment using Ethereum blockchain. EAI Endorsed Transactions on Scalable Information Systems, 11(2), 2024.
  • Arali, N., Narayan, D.G., & Hiremath, P.S.
  • An efficient and secure blockchain consensus algorithm using game theory. International Journal of Computer Network and Information Security, 16(2), 2024.
  • Narayan, D.G., Arali, N., & Tejas, R.
  • DPoSEB: Delegated proof of stake with exponential backoff consensus algorithm for Ethereum blockchain. Computer Science Journal of Moldova, 32(2), 2024.
  • Narayan, D.G., Heena, M., & Amit, K.
  • A collaborative approach for detection of DDoS attacks in SDN using entropy and deep learning. Journal of Telecommunications and Information Technology, 2024. (Accepted)
  • Jacob, J., Shinde, S., & Narayan, D.G.
  • An efficient controller placement algorithm using clustering in software defined networks. Journal of Telecommunications and Information Technology, 4, 2023: 9–17.
  • Patil, S., Narayan, D.G., Bhat, A., Hungund, A., & Patil, D.M.
  • Horizontal pod autoscaling in Kubernetes cluster using Long Short-Term Memory. Lecture Notes in Electrical Engineering, vol. 1189 LNEE, 2024: 461–471.
  • Patil, R., & Narayan, D.G.
  • Mitigation of DDoS attacks using entropy and proof-of-work based puzzle in OpenStack cloud. In Proceedings of the 2023 3rd International Conference on Intelligent Technologies (CONIT), 2023.
  • RESEARCH FOCUS AREAS

Domains of Impact

01

Edge AI

02

High Performance Computing

03

Data Science

04

Cloud Computing