M.Tech in Digital Communications
B.Tech in Electronics and Communication Engineering
RESEARCH INTERESTS
Signal and Image Processing
39
Scopus Publications
482
Scholar Citations
13
Scholar h-index
13
Scholar i10-index
Scopus Publications
Deep Learning Approach for Breast Cancer Malignancy Identification Using a Tailored CNN Nuneti Govardhan, Ch. Rajendra Prasad, Raj Kumar K, Eelandula Kumaraswamy Proceedings of 2nd International Conference on Visual Analytics and Data Visualization Icvadv 2026, 2026 Breast cancer (BC) is one of the world's top causes of death for women, and as patient survival rates rise, early detection of dangerous tumors is crucial. Traditional diagnostic techniques frequently depend on the manual interpretation of medical images, which can be laborious and lead to human error. The current research proposes to employ a deep learning customized Convolutional Neural Network architecture (CNN) to automatically detect the malignancy of breast cancer. To enhance the classification accuracy between the benign and malignant cases, the proposed model is specifically designed to derive discriminative features of histopathology images. Layer tuning, dropout regularization, and adaptive learning rate modifications are used to enhance the network's architecture in order to promote generalization and avoid overfitting. In terms of accuracy (94.1%), sensitivity (benign) (94.4%), precision (malignant) (96.8%), sensitivity (malignant) (94.4%), and F1-Score (malignant) (95.6%), the customized CNN's experimental results on the BreakHis dataset demonstrate superiority over conventional pre-trained models. The findings suggest that the proposed strategy will provide a powerful and reliable tool to assist doctors in diagnosing breast cancer at an early stage, which will lead to better and more accurate clinical decision-making.
AI-Assisted Breast Cancer Prediction, Classification, and Future Directions: A Narrative Review Involving Histopathological Image Datasets Govardhan Nuneti, Rajendra Prasad Ch, Raj Kumar K, Kumara Swamy E. Open Public Health Journal, 2025 Breast cancer-related deaths in women have increased significantly in the past decade, emphasizing the need for an accurate and early diagnosis. AI-assisted diagnosis using deep learning and machine learning (DML) approaches has become a key method for analysing breast tissue and identifying tumour stages. DML algorithms are particularly effective for classifying breast cancer tissue images due to their ability to handle large datasets, work with unstructured data, generate automated features, and improve over time. However, the performance of these models is heavily on the datasets used for training, with the models performing inconsistently between different datasets. Given the prediction that by 2050, there will be more than 30 million new cancer cases and more than 10 million deaths worldwide, it is crucial to focus on recent advancements in DML algorithms and histopathological image datasets used in AI-assisted systems. Histopathological images provide critical information to identify tissue abnormalities, which directly impact model performance. This review discusses and analyses various DML-based models and the datasets used in their implementation, highlighting research gaps and offering suggestions for future improvements. The goal is to develop more effective and efficient approaches for the prediction of early-stage breast cancer. In addition, this early detection assists the healthcare professional in guiding prevention methods in smart healthcare systems.
Deep Learning Approach for Breast Cancer Malignancy Identification Using a Tailored CNN N Govardhan, CR Prasad, E Kumaraswamy 2026 International Conference on Visual Analytics and Data Visualization … , 2026 2026
IoT based flood control system in farm field M Kommabatla, P Krishna, E Kumaraswamy, M Sujatha, P Prathyusha AIP Conference Proceedings 2971 (1), 050021 , 2024 2024
Development of smart and secure system for women safety P Prathyusha, M Kommabatla, P Krishna, E Kumaraswamy, VC Rao AIP Conference Proceedings 2971 (1), 050022 , 2024 2024
Deep learning approach for detection of ECG abnormalities E Kumaraswamy, M Ramu, IR Reddy, G Aruna, N Govardhan AIP Conference Proceedings 2971 (1), 050006 , 2024 2024
Classification of diabetes mellitus prediction using hybrid machine learning techniques G Aruna, M Umalwara, V Tejaswini, E Kumaraswamy, S Ghate, M Rajesh AIP Conference Proceedings 2971 (1), 020002 , 2024 2024 Citations: 3
Advanced machine learning techniques for satellite image processing E Kumaraswamy, M Kommabatla, IR Reddy, R Karre, S Kasanagottu, ... AIP Conference Proceedings 2971 (1), 050020 , 2024 2024
Simulators for vehicular ad hoc network (VANET) development N Govardhan, E Kumaraswamy, IR Reddy, M Kommabatla AIP Conference Proceedings 2971 (1), 050007 , 2024 2024
Application of machine learning algorithms in a smart home design S Kasanagottu, R Karre, E Kumaraswamy AIP Conference Proceedings 2971 (1), 050012 , 2024 2024 Citations: 1
Advanced e-health care system using IOT in blockchain R Karre, S Kasanagottu, M Kommabatla, C Padmaja, M Sujatha, ... AIP Conference Proceedings 2971 (1), 050008 , 2024 2024
Applications of AI and ML techniques for 5G wireless communications M Ramu, E Kumaraswamy, K Mahender, N Govardhan AIP Conference Proceedings 2971 (1), 050014 , 2024 2024 Citations: 2
Underwater image enhancement using teleost fish retinal mechanism M Ramu, E Kumaraswamy, N Govardhan AIP Conference Proceedings 2971 (1), 050013 , 2024 2024
Performance Analysis of Feature Extraction and Deep Learning Approaches on Whole and Segmented Histopathological Images for Cancer Grade Classification E Kumaraswamy, S Kumar, S Sharma 2024 IEEE International Conference on Interdisciplinary Approaches in … , 2024 2024 Citations: 4
An invasive ductal carcinomas breast cancer grade classification using an ensemble of convolutional neural networks E Kumaraswamy, S Kumar, M Sharma Diagnostics 13 (11), 1977 , 2023 2023 Citations: 34
Retrospective Study of Convolutional Neural Network for Medical Image Analysis and a Deep Insight Through Histopathological Dataset S Sharma, E Kumaraswamy, S Kumar Computational Intelligence: Select Proceedings of InCITe 2022, 47-58 , 2023 2023 Citations: 7
An empirical study of various face recognition and face liveness detection techniques and algorithms V Sivalenka, S Aluvala, Y Sneha, K Mannan, S Farheen, E Kumaraswamy AIP Conference Proceedings 2418 (1), 020056 , 2022 2022 Citations: 9
Digital watermarking techniques: Comparative analysis and robustness for real time applications E Kumaraswamy, K Mahender, CR Prasad, N Govardhan, BP Yadav AIP Conference Proceedings 2418 (1), 030070 , 2022 2022 Citations: 21
Forecast the death and recovery rate of COVID 2019 using ARIMA and PROPHET models S Sirikonda, SN Kumar, T Sravanthi, J Srinivas, ST Manchikatla, ... AIP Conference Proceedings 2418 (1), 020055 , 2022 2022 Citations: 31
IoT based indoor air quality monitoring and purification system with serial UV lights E Sudarshan, K Anusha, BP Yadav, PA Kishan, E Kumaraswamy AIP Conference Proceedings 2418 (1), 020059 , 2022 2022 Citations: 2
Privacy-preserving in IoT with medical data sharing in limited computing power M Sruthi, R Netravathi, D Ramesh, E Kumaraswamy AIP Conference Proceedings 2418 (1), 020063 , 2022 2022 Citations: 1
Design and fabrication of rectangular microstrip patch antenna at ISM band for medical applications E Thangaselvi, E Kumaraswamy, K Ramamoorthy, S Karthikeyan, ... AIP Conference Proceedings 2418 (1), 030015 , 2022 2022 Citations: 2
MOST CITED SCHOLAR PUBLICATIONS
Confluence of Machine Learning with Edge Computing for IoT Accession K Mannanuddin, S Aluvala, Y Sneha, E Kumaraswamy, E Sudarshan, ... IOP Conference Series: Materials Science and Engineering 981 (4), 042003 , 2020 2020 Citations: 71
Digital Watermarking: State of The Art and Research Challenges in Health Care & Multimedia Applications E Kumaraswamy, GM Kumar, K Mahender, K Bukkapatnam, CR Prasad IOP Conference Series: Materials Science and Engineering 981 (3), 032031 , 2020 2020 Citations: 60
Svd based robust unsighted video watermarking technique for different attacks E Kumaraswamy, R Vatti, G Vallathan, CR Prasad, KR Danthamala IOP Conference Series: Materials Science and Engineering 981 (3), 032030 , 2020 2020 Citations: 41
An invasive ductal carcinomas breast cancer grade classification using an ensemble of convolutional neural networks E Kumaraswamy, S Kumar, M Sharma Diagnostics 13 (11), 1977 , 2023 2023 Citations: 34
A prediction based encryption approach for telemedicine applications G Vallathan, T Rajani, E Kumaraswamy, C Srinivas IOP Conference Series: Materials Science and Engineering 981 (3), 032008 , 2020 2020 Citations: 33
Smart Traffic Junction Using Raspberry Pi G Mahesh Kumar, E Kumaraswamy IOP Conference Series: Materials Science and Engineering 981 (3), 032048 , 2020 2020 Citations: 33
Smart memory management (SaMM) for embedded systems without MMU K Bukkapatnam, Prashant, CK Rekha, E Kumaraswamy, R Vatti IOP Conference Series: Materials Science and Engineering 981 (3), 032010 , 2020 2020 Citations: 32
Forecast the death and recovery rate of COVID 2019 using ARIMA and PROPHET models S Sirikonda, SN Kumar, T Sravanthi, J Srinivas, ST Manchikatla, ... AIP Conference Proceedings 2418 (1), 020055 , 2022 2022 Citations: 31
A review on cancer detection strategies with help of biomedical images using machine learning techniques E Kumaraswamy, S Sharma, S Kumar AIP Conference Proceedings 2418 (1), 030064 , 2022 2022 Citations: 25
Digital watermarking techniques: Comparative analysis and robustness for real time applications E Kumaraswamy, K Mahender, CR Prasad, N Govardhan, BP Yadav AIP Conference Proceedings 2418 (1), 030070 , 2022 2022 Citations: 21
Key challenges in the diagnosis of cancer using artificial intelligence methods E Kumaraswamy AIP Conference Proceedings 2418 (1), 030049 , 2022 2022 Citations: 19
Invasive ductal carcinoma grade classification in histopathological images using transfer learning approach E Kumaraswamy, S Sharma, S Kumar 2021 IEEE Bombay section signature conference (IBSSC), 1-6 , 2021 2021 Citations: 14
Forecasting the spread of Covid-19 pandemic outbreak in India using ARIMA time series modelling P Sarla, S Rakmaiah, RA Reddy, A Rajesh, E Kumaraswamy, Navya, ... AIP Conference Proceedings 2418 (1), 060003 , 2022 2022 Citations: 13
An empirical study of various face recognition and face liveness detection techniques and algorithms V Sivalenka, S Aluvala, Y Sneha, K Mannan, S Farheen, E Kumaraswamy AIP Conference Proceedings 2418 (1), 020056 , 2022 2022 Citations: 9
A smart automatic sanitizer dispenser and body temperature inspection machine E Sudarshan, K Sarma, K Sujatha, D Kothandaraman, E Kumaraswamy AIP Conference Proceedings 2418 (1), 020061 , 2022 2022 Citations: 9
Retrospective Study of Convolutional Neural Network for Medical Image Analysis and a Deep Insight Through Histopathological Dataset S Sharma, E Kumaraswamy, S Kumar Computational Intelligence: Select Proceedings of InCITe 2022, 47-58 , 2023 2023 Citations: 7
The prediction of No 2 and O 3 concentrations in ambient air using soft computing techniques for hyderabad model P Bojja, V Divya, MGM Naidu, G Ashok, E Kumaraswamy AIP Conference Proceedings 2418 (1), 030016 , 2022 2022 Citations: 7
Performance Analysis of Feature Extraction and Deep Learning Approaches on Whole and Segmented Histopathological Images for Cancer Grade Classification E Kumaraswamy, S Kumar, S Sharma 2024 IEEE International Conference on Interdisciplinary Approaches in … , 2024 2024 Citations: 4
AIP Conference Proceedings E Kumaraswamy, S Sharma, S Kumar AIP Publishing LLC, 2418, 030049 , 2022 2022 Citations: 4
Classification of diabetes mellitus prediction using hybrid machine learning techniques G Aruna, M Umalwara, V Tejaswini, E Kumaraswamy, S Ghate, M Rajesh AIP Conference Proceedings 2971 (1), 020002 , 2024 2024 Citations: 3