0000-0001-7410-3633 About
I am a researcher specializing in computer vision, deep learning, machine learning, and image processing, with a strong focus on applying AI to biomedical imaging, cybersecurity, and real-world problem-solving. Currently, I am affiliated with the Indian Institute of Technology (IIT), where my work involves designing novel deep learning architectures, optimizing neural networks for medical diagnostics, and developing AI-driven cybersecurity solutions.
My research primarily focuses on biomedical image analysis, including liver tumor segmentation, breast cancer classification, pneumonia detection, and glaucoma segmentation. I have contributed to innovative AI frameworks such as CICADA (UCX) for breast cancer classification and UIGO networks for medical segmentation, integrating hybrid deep learning models to enhance medical diagnostics. Additionally, I have worked extensively on seizure detection using EEG signals, utilizing cross-domain feature extraction techniques for improving classification accuracy.
Beyond healthcare AI, I have a strong foundation in cybersecurity and anomaly detection, with expertise in PKI infrastructure, digital certificates, authentication protocols, and AI-powered threat detection. My work extends to computer vision applications, including gesture recognition, deep belief networks for visual learning, and AI-driven analysis of driving behavior.
I have published my research in peer-reviewed journals and international conferences, covering topics such as:
- Deep learning for disease classification and medical imaging
- Hybrid optimization techniques for feature selection and segmentation
- AI-based EEG signal analysis for seizure detection
- AI-driven cybersecurity and anomaly detection
- Computer vision applications in healthcare and real-world AI
### Selected Publications
Banerjee, T., Jain, A., Sethuraman, S.C., Satapathy, S.C. & Karthikeyan, S. (2022) ‘Deep Convolutional Neural Network (Falcon) and transfer learning‐based approach to detect malarial parasite’, *Multimedia Tools and Applications*, 81(10), pp. 13237-13251.
Banerjee, T., Batta, D., Jain, A., Karthikeyan, S., Mehndiratta, H. & Hari Kishan, K. (2021) ‘Deep belief convolutional neural network with artificial image creation by GANs based diagnosis of pneumonia in radiological samples of the pectoralis major’, in *Innovations in Electrical and Electronic Engineering: Proceedings of ICEEE*.
Banerjee, T., Srikar, K.V.P., Reddy, S.A., Biradar, K.S., Koripally, R.R. & Varshith, G. (2021) ‘Hand sign recognition using infrared imagery provided by Leap Motion Controller and computer vision’, *2021 International Conference on Innovative Practices in Technology and Management (ICIPTM)*.
Banerjee, T., Karthikeyan, S., Sharma, A., Charvi, K. & Raman, S. (2022) ‘Attention-Based Discrimination of Mycoplasma Pneumonia’, in *Proceedings of International Conference on Computational Intelligence and Data Science (ICCIDS 2022)*.
Saminathan, K., Banerjee, T., Rangasamy, D.P. & Cruz, M.V. (2024) ‘Segmentation of Thoracic Organs through Distributed Extraction of Visual Feature Patterns Utilizing Resio-Inception U-Net and Deep Cluster Recognition Techniques’, *Current Gene Therapy*, 24(3), pp. 217-238.
Banerjee, T., Narula, G.S. & Wason, R. (2024) ‘HHO-UNet-IAA: Harris Hawks Optimization-based Novel UNet-Inception Attention Architecture for Glaucoma Segmentation’, [Journal Name Pending].
Karthikeyan, S., Banerjee, T., Sathya, K. & Sumathi, A.C. (2022) ‘Separable CNN-based Automated Classification of WBCs in Peripheral Blood Stream’, *NeuroQuantology*, 20(8), p. 394.
Banerjee, T., Sharma, A., Charvi, K., Raman, S., Regalla, R.G. & Sindhupriya, T. (2022) ‘Journey of Letters to Vectors Through Neural Networks’, in *Proceedings of Data Analytics and Management: ICDAM 2021, Volume 1*, pp. 709-717.
Karthikeyan, S., Gopikrishnan, S. & Batta, D. (2021) ‘Double Helical Ensemble Multi-Dimensional 4-D Structured Neural Network to Analyze the Driving Pattern, Driver DNA and Generate License Score using Smartphone Sensor Data’, *Turkish Journal of Computer and Mathematics Education (TURCOMAT)*, 12(13).
Banerjee, T., Batta, D., Jain, A., Biradar, K.S., Koripally, R.R. & Srikar, K.V.P. (2021) ‘Deep Belief Convolutional Neural Network for Diagnosis of Pneumonia: A Response to Coronavirus’, *2021 International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)*.
Peesa, R.B., Satpathy, A., Karthikeyan, S., Bisht, M., Banerjee, T. & Gupta, G. (2020) ‘Single Node Hadoop Cluster for Small Scale Industrial Automation’, *2020 IEEE 5th International Conference on Computing, Communication and Automation (ICCCA)*.
Banerjee, T., Karthikeyan, S. & Bhargav, R. (2020) ‘Deep belief CNN-based computer vision’, *Test Engineering and Management*, 83 (March-April), pp. 5111-5119.
Employment
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Indian Institute of Technology Patna Research Scholar2025 - Present
Education
Education history is unavailable.
Projects & Funding
Projects & funding information is unavailable.
Publications (14)
- Towards accurate and interpretable brain tumor diagnosis: T-FSPANNet with Tri-Attribute and pyramidal attention-based feature fusion Save
- A Comprehensive Review of LLM-based Text-to-SQL Systems: Methods, Datasets, and Trends Save
- Hawk-Swarmception Segmentation Network (HSCS-Net): Enhanced Liver Tumor Segmentation with Receptive Field Optimization and Clinical Data-Guided Feature Selection via PSO and GWO Save
- Towards automated and reliable lung cancer detection in histopathological images using DY-FSPAN: A feature-summarized pyramidal attention network for explainable AI Save
- Electromagnetic Interaction Algorithm (EIA)‐Based Feature Selection With Adaptive Kernel Attention Network (AKAttNet) for Autism Spectrum Disorder Classification Save
- Segmentation of Thoracic Organs through Distributed Extraction of Visual Feature Patterns Utilizing Resio-Inception U-Net and Deep Cluster Recognition Techniques Save
- HHO-UNet-IAA: Harris Hawks Optimization based Novel UNet-Inception Attention Architecture for Glaucoma Segmentation Save
- Attention-Based Discrimination of Mycoplasma Pneumonia Save
- Deep Convolutional Neural Network (Falcon) and transfer learning‐based approach to detect malarial parasite Save
- Journey of Letters to Vectors Through Neural Networks Save