• M.Vamsi Krishna, Srinivasa Rao Battula, “Detection and diagnosis of diabetic eye diseases using two phase transfer learning approach”, PeerJ Computer Science(2024).https://doi.org/10.7717/peerj-cs.2135(SCIE -IF 3.8)
• Swathi, B., Kolisetty, S.S., Sivanarayana, G.V., B.Srinivasa Rao. Efficientnetv2-RegNet: an effective deep learning framework for secure SDN based IOT network. Cluster Computing (2024). https://doi.org/10.1007/s10586-024-04498-0 (SCI IF - 3.6)
• B. S. Rao and M. Aparna, "A Review on Alzheimer’s Disease Through Analysis of MRI Images Using Deep Learning Techniques", in IEEE Access, vol. 11, pp. 71542-71556, 2023, doi: 10.1109/ACCESS.2023.3294981. (SCIE IF- 3.9)
• BS Rao, Mudiyala Aparna, Jonnadula Harikiran & Tatireddy Subba Reddy (2023) An effective Alzheimer’s disease segmentation and classification using Deep ResUnet and Efficientnet, Journal of Biomolecular Structure and Dynamics, DOI: 10.1080/07391102.2023.2294381 (SCI-IF 4.1)
• Harikiran, J., B. Sai Chandana, B. Srinivasarao, B. Raviteja, and Tatireddy Subba Reddy. "Software Defect Prediction Based Ensemble Approach." Computer Systems Science & Engineering Vol.46, no. 1 (2023) (SCI-IF 4.39)
• Pechetti S, Rao BS. 2023. Optimized MobileNetV3: a deep learning-based Parkinson’s disease classification using fused images. PeerJ Computer Science 9:e1702 https://doi.org/10.7717/peerj-cs.1702 (SCIE -IF 3.8)
• Rao, Battula Srinivasa;Aparna, Mudiyala;Kolisetty, Soma Sekhar;Janapana, Hyma;Koteswararao, Yannam Vasantha, “Multi-class Classification of Alzheimer's Disease Using Deep Learning and Transfer Learning on 3D MRI Images” Traitement du Signal, 2024, v. 41, n. 3, p. 1397, doi. 10.18280/ts.410328 (SCI IF-2.4)
• Bairaboina, Sai Samba Siva Rao, and Srinivasa Rao Battula, "An Effective WBC Segmentation and Classification Using MobilenetV3–ShufflenetV2 Based Deep Learning Framework", IEEE Access, vol. 11, pp. 27739-27748, 2023. doi: 10.1109/ACCESS.2023.3259100 (SCIE IF- 3.9)
• Bairaboina, Sai Sambasiva Rao, and Srinivasa Rao Battula. 2023. "Ghost-ResNeXt: An Effective Deep Learning Based on Mature and Immature WBC Classification" Applied Sciences – MDPI Vol. 13, no. 6: 4054. https://doi.org/10.3390/app13064054 (SCI IF-2.8)
• M. Aparna and B. S. Rao, "Xception-fractalnet: hybrid deep learning based multi-class classification of Alzheimer’s disease", Computers, Materials & Continua, vol. 74, no.3, pp. 6909–6932, 2023., DOI: 10.32604/cmc.2023.034796.(SCI IF-3.8)
• M Siva Naga Raju, Srinivasa Rao Battula “An Hybrid PCANet- Extreme Learning Machine for Lung and Colon Cancer Classification” Concurrency and Computation: Practice and Experience, 35(8), e7361, DOI: https://doi.org/10.1002/cpe.7361 (SCI IF-1.8)
• Mudiyala Aparna, Srinivasa Rao Battula “Classification of Alzheimer’s Disease through analysis of MRI images using Two-Phase Transfer Learning”, Traitment du Signal (SCI Accepted IF-2.4).
• M.Vamsi Krishna, Srinivasa Rao Battula “An approach to Classify and Segment of Diabetic Retinopathy and Retinopathy of Prematurity” Traitment du Signal (SCI Accepted IF-2.4)
• J. Harikiran, B. Sai Chandana, B. Srinivasa Rao, B. Ravi Teja “Ocular disease examination of fundus images by hybriding SFCNN and rule mining algorithms” The Imaging Science Journal, 06 Mar 2023, https://doi.org/10.1080/13682199.2023.2183456 (SCI Accepted)
• M Siva Naga Raju, Dr. B. Srinivasa Rao,” Medical Image Analysis using Transfer Learning Approaches: An Outlook”. Traitement du Signal, 39(5),1463-1474, DOI: https://doi.org/10.18280/ts.390502, (SCI- IF-2.29)
• Raju, M. S.N, & Rao, B. S. (2022). “Colorectal Cancer Disease Classification Using Mobilenetv2 Based on Deep Learning”. International Journal of Software Innovation (IJSI), 10(1), 1-18. http://doi.org/10.4018/IJSI.309725. (SCI)
• Aparna, M., & Rao, S. B. (2022). A Hybrid Siamese-LSTM (Long Short-Term Memory) for Classification of Alzheimer's Disease. International Journal of Software Innovation (IJSI), 10(1), 1-14, DOI: 10.4018/IJSI.309720 (ESCI)
• M Siva Naga Raju, Dr. B. Srinivasa Rao – "Classification of Colon and Lung cancer through analysis of Histopathology images using Deep Learning Models", Ingénierie des Systèmes d'Information, 27(6), 967-971, DOI: 10.18280/isi.270613
• Mudiyala Aparna, Battula Srinivasa Rao – "A novel automated deep learning approach for Alzheimer's disease classification", IAES International Journal of Artificial Intelligence (IJ-AI), Vol. 12, No. 1, March 2023, pp. 451~458, DOI: 10.11591/ijai.v12.i1.pp451-458
• Bairaboina, Sai Sambasiva Rao, and Srinivasa Rao Battula – "Efficientnet - Xgboost: An Effective White Blood Cell Segmentation and Classification" – Nano Biomedicine and Engineering (NBE) – (Scopus Indexed Accepted for Publication)
• Mudiyala Aparna, Battula Srinivasa Rao – "Detection and Diagnosis of Diabetic Retinopathy Using Transfer Learning Approach" International Journal of Intelligent Engineering and Systems, Vol.16, No.3, 2023 (Scopus Indexed)
• Raju, M. Siva Naga, and B. Srinivasa Rao – "Colorectal Cancer Disease Classification and Segmentation Using A Novel Deep Learning Approach.", International Journal of Intelligent Engineering and Systems, Vol.15, No.4, 2022, DOI: 10.22266/ijies2022.0831.21 (Scopus Indexed)
• Raju, Mallela Siva Naga, and Battula Srinivasa Rao – "Colorectal multi-class image classification using deep learning models." Bulletin of Electrical Engineering and Informatics 11.1 (2022): 195-200. DOI: 10.11591/eei.v11i1.3299 (Scopus Indexed)
• Follicle Detection in Ultrasound Images using Adaptive Clustering Algorithms and Empirical Mode Decomposition, J. Harikiran, E. Vamsidhar, B. Srinivasa Rao, B. Saichandana, International Journal of Innovative Technology and Exploring Engineering, Volume-9 Issue-2, 2019
• B. Sai Chandana, K. Mallikarjun Rao, J. Hari Kiran, B. Srinivasa Rao – Dimensionality Reduction and Hierarchical clustering in framework for Hyperspectral Image Segmentation, Bulletin of Electrical Engineering and informatics, Volume -8, Number-1, 2019 (Scopus Indexed)
• B. Srinivasa Rao, E.Srinivasa Reddy – "HSO based FCM with active contours for Glioblastoma Multiform Tumor segmentation", Journal of Engineering and Applied Science, Volume 11, Issue 6, pages 1338-1348, 2016. (Scopus Indexed)
• B. Srinivasa Rao, E. Srinivasa Reddy – "EMD based Fuzzy C-Means clustering algorithm for medical image segmentation", IJAER 2015 Volume 10, Issue 20, pages: 41400-41405 (Scopus Indexed)
• B. Srinivasa Rao, E. Srinivasa Reddy – "A Novel Fast FCM clustering for Segmentation of Salt and Pepper noise corrupted images", Springer India 2014 volume2, Pages:381-391 (Scopus Indexed)
• B. Srinivasa Rao, E. Srinivasa Reddy – "An Efficient Anti-noise Fast FCM Clustering for Glioblastoma Multiforme Tumor Segmentation", IJCSIS, Volume 14, Issue 4, 2016 (Scopus Indexed)
• B. Srinivasa Rao, E. Srinivasa Reddy “A New Affinity Propagation clustering with active contours for automatic segmentation of GBM tumors in MR Images, IJSER, VOL.8, ISSUE.1, pages: 1020-1024, 2017
• B. Srinivasa Rao, E. Srinivasa Reddy, “OBL-GA based FCM with level sets for automatic segmentation of GBM tumors. (Accepted IJCSE, Volume-5, Issue-1, January 2017)
• B. Srinivasa Rao, E. Sreenivasa Reddy, “A survey on Glioblastoma Multiforme Tumor Segmentation through MR images”, IJSER, VOL.7, ISSUE.2, pages: 1311-1322, 2016
• B. Sai Chandana, B. Srinivasa Rao, K. Srinivas, R. Kiran Kumar, “K-means with Empirical Mode Decomposition for Classification of Remote Sensing Image”, Volume 3, No. 5, Sept-Oct 2012, pages: 245-248
• S. Anjali Devi, R. Venu Babu, B. Srinivasa Rao “A new approach for Evolution of end to end Security in Wireless Sensor Network”, International Journal on Computer Science and Engineering, Vol. 3 No. 6 June 2011, pages: 2531-2543

• A S Vidyn, B. Srinivasa Rao “Automated Detection and Classification of COVID-19 Based on CT Images Using Deep Learning Mode”, Springer - Lecture Notes in Electrical Engineering (LNEE-2021) - Bangalore
• T. Subha Mastan Rao, B. Jhansi Vazram, S Anjali Devi, B. Srinivasa Rao “A Novel Approach for Detecting Traffic Signs using Deep Learning”, 2021 IEEE Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)
• B. Srinivasa Rao, E. Sreenivasa Reddy “A novel automated Fast FCM clustering algorithm for segmentation of Salt and Pepper corrupted Images”, Springer Computational Intelligence in Datamining (ICCIDM 2015)
• T. Subbareddy, J. Harikiran, B. Srinivasa Rao “Gridding and Supervised Segmentation method for DNA Micro Array Images”, Proceedings of International Conference on Computational Intelligence and Data Engineering, Springer, ICCIDE 2020
• A.S Vidyn, B. Srinivasa Rao “Histopathological Image Classification using Deep Neural Network with Fine-Tuning”, International Conference on Data Engineering and Intelligent Computing, Proceedings of AISC, Springer 2021
• M. Siva Nagaraju, B. Srinivasa Rao “Classification of Colon Cancer through analysis of histopathology images using Transfer Learning”, 2022 IEEE 2nd International Symposium on Sustainable Energy, Signal Processing and Cyber Security (iSSSC)
• Chavva Subba Reddy, Dr. S. Ravi Sankar, Dr. B. Srinivasa Rao “A Survey on Business Intelligence Tools for Marketing, Financial and Transportation Services”, Springer Smart Intelligent Computing and Applications, 2018
• Participated and presented a technical paper on in the Conference IETE Zonal seminar on Emerging and converging communication Technologies “Dynamic path-based software watermarking”, 10-11-02-2007

Patents Published

Published 7 Indian patents.