Improved Sleep Stage Classification using Machine Learning with Data Augmentation G.L.N. Murthy, J. Divya Latha, G. Hemanth, S. Sindhuja Proceedings of 5th International Conference on Soft Computing for Security Applications Icscsa 2025, 2025 Accurate sleep stage classification is essential for diagnosing sleep disorders and understanding sleep patterns. Scarcity of desired data is the fundamental constrain in automated classification algorithms. In particular when it is required to deal bio medical signal, the accuracy is much needed. The current proposes a solution for this problem through a novel machine learning-based approach to enhance classification accuracy using Support Vector Machine (SVM) and Random Forest (RF) models, combined with data augmentation techniques such as time warping and signal permutation. The Sleep-EDF dataset was used for model training and evaluation, ensuring robust validation of the proposed methodology. Experimental results demonstrate that the proposed approach achieves a classification accuracy of 95%, surpassing traditional methods. The integration of data augmentation improves feature diversity, enhancing model generalization and performance. Additionally, the proposed framework enables real-time monitoring, making it suitable for practical applications in sleep health assessment. These findings highlight the potential of machine learning and augmentation techniques in advancing automated sleep stage classification.
LSTM and CNN based Speech Emotion Recognition a New Paradigm in Deep Learning G.L.N. Murthy, Ch. Yagnitha, Sk. Nafia, J.Divya Latha Indiscon 2025 IEEE 6th India Council International Subsections Conference Proceedings, 2025 Identifying the emotions hidden in speech (SER) encounters difficulties in virtue of the subjective and variable nature of human emotions, along with limitations such as data dependency, biases from training data, and a restricted range of emotion categories. Machine learning-based SER employs algorithms to classify emotional content in spoken language, with deep learning methods, notably LSTM-RNNs, gaining traction for their adeptness in capturing temporal dependencies in audio data. Despite this, they still confront issues like data dependency and inherited biases. To mitigate these limitations, a hybrid algorithm comprising LSTM-RNNs to address the drawbacks of existing SER algorithms. By focusing on temporal interdependencies, LSTM-RNNs offer a remedy to the vanishing gradient problem inherent in long-range dependencies. The proposed system with an accuracy of 96.34 %, seeks to overcome these shortcomings, presenting a more robust and precise method for SER, promising advancements in human-computer interaction, healthcare, security, and entertainment sectors.
Alzheimer image registration using hybrid random forest and deep regression network algorithm Ramakoteswararao Siddabathuni, Sivagurunathan Palanivel, Godavarthi Lakshmi Narasimha Murthy Indonesian Journal of Electrical Engineering and Computer Science, 2024 <span>Image registration involves superimposing images (two or more) of similar background obtained at various periods of time, at different angles, and/or with various detectors. Geometrical alignment of two scans, reference image as well as capture image. The current dissimilarity between images is because of distinct image conditions. Image registration is difficult step in image analysis works on change detection, image fusion as well as <br /> multi-channel images recovery to obtain concluded data from integration of different sources. In this analysis image registration using hybrid random forest (RF) and deep regression network algorithm for magnetic resonance imaging (MRI) applications is implemented. The Alzheimer’s disease neuroimaging initiative (ADNI) database provided by the dataset utilised in this implementation. From results it can observe that compared with individual random of forest, Hybrid RF and deep regression network algorithm improves the accuracy, precision and F1-score in effective way.</span>
Automated hydroponic nutrient control system for smart agriculture Ambidi Naveena, Shaik Nannu Saheb, Ratnababu Mamidi, Godavarthi Lakshmi Narasimha Murthy Indonesian Journal of Electrical Engineering and Computer Science, 2024 <p><span>Hydroponics is a type of soil-free farming that uses less water and other resources than conventional soil-based farming methods. Hydroponic cultivation system has high yield per acre of land with minimal consumption of water and can be a possible to meet the growing food demand of the world. The hydroponic plants fertility must be preserved, proper nutrition, a environmental temperature, and nutrient stability are crucial. It will be simpler for a farmer to keep track of all hydroponic plants by automatically monitoring nutrient flow and ambient temperature stability. By implementing artificial intelligence-based regulating algorithms in the agriculture industry, recent technology advancements are highly helpful in resolving these issues. This paper presents, automated hydroponic nutrient control system (AHNCS) for smart agriculture. System architecture is consisting of sensors network, Raspberry pi 4 microcontroller and actuators. Raspberry pi 4 microcomputer read sensor values from sensors process and activates particular actuator. The automation of the hydroponic system helps to avoid human intervention. The utilization of sensors and actuators, promptly act for the needs of the plant without any delay. The AHNCS having high accuracy, high efficiency and less delay. Hence, automation of the existing hydroponic system can reduce human dependency, provide accurate results, constant monitoring of plant health.</span></p>
Delineation of putamen from the brain magnetic resonance image for Parkinson disease related applications International Journal of Advanced Science and Technology, 2020
A depth based nonlinear filtering for MR images International Journal of Applied Engineering Research, 2014
RECENT SCHOLAR PUBLICATIONS
An intelligent multimodal medical image registration using hybrid meta-heuristic optimization with transformer-based residual UNet S Ramakoteswararao, S Palanivel, GLN Murthy Pattern Recognition 172, 112708 , 2026 2026 Citations: 2
Detection Of Voice Disorders Using Machine Learning with Data Augmentation GLN Murthy, YL Priya, GV Kumar, KS Kumar 2026 8th International Conference on Devices, Circuits, and Systems (ICDCS), 1-6 , 2026 2026
ATUN-MDC image registration: Performance enhancement of medical image registration using adaptive TransUNet with multi-dilated convolution model S Ramakoteswararao, S Palanivel, GLN Murthy Biomedical Signal Processing and Control 111, 108392 , 2026 2026
A novel machine learning framework: cross transformer based optimization model for the detection and classification of brain tumor using clinical decision analysis AVR Mayuri, SP Maniraj, M Duraisamy, GLN Murthy, K Garg, ... International Journal of Machine Learning and Cybernetics 16 (10), 8331-8358 , 2025 2025 Citations: 2
TransDense121-UNet: a multi-scale transformer-based approach for accurate liver tumor segmentation AVR Mayuri, SP Maniraj, M Duraisamy, GLN Murthy, K Garg, ... Evolving Systems 16 (3), 96 , 2025 2025 Citations: 1
LSTM and CNN based Speech Emotion Recognition a New Paradigm in Deep Learning GLN Murthy, C Yagnitha, S Nafia, JD Latha 2025 IEEE 6th India Council International Subsections Conference (INDISCON), 1-6 , 2025 2025
Improved Sleep Stage Classification using Machine Learning with Data Augmentation GLN Murthy, JD Latha, G Hemanth, S Sindhuja 2025 5th International Conference on Soft Computing for Security … , 2025 2025
Improved LSTM-Squeeze net architecture for brain activity detection using EEG with improved feature set SKM Sharif, R Butta, DV Rao, GLN Murthy, NM Devarajan Biomedical Signal Processing and Control 101, 107222 , 2025 2025 Citations: 5
Ensemble deep learning approach for early diagnosis of Alzheimer's disease R Butta, MS Shaik, GLN Murthy Multimedia Tools and Applications 84 (3), 1403-1428 , 2025 2025 Citations: 5
Alzheimer image registration using hybrid random forest and deep regression network algorithm R Siddabathuni, S Palanivel, GLN Murthy Indonesian Journal of Electrical Engineering and Computer Science 33 (2 … , 2024 2024 Citations: 2
Deep learning based classification of covid-19 severity using hierarchical deep maxout model MSB Rao, YM Rao, C Venkataiah, GLN Murthy, M Dharani, M Jayamma Biomedical Signal Processing and Control 88, 105653 , 2024 2024 Citations: 10
An MFCC based machine learning frame work for neuromuscular disorder detection GLN Murthy, K Dharani, ED Likhith, KRT Rao, M Sandeep INTERNATIONAL CONFERENCE ON ADVANCES IN SIGNAL PROCESSING COMMUNICATIONS AND … , 2023 2023
A machine learning based frame work for classification of neuromuscular disorders GLN Murthy, GP Saii, T Pavani, JL Mohan 2022 IEEE 1st International Conference on Data, Decision and Systems (ICDDS … , 2022 2022 Citations: 4
Review on Detection of Neuromuscular Disorders Using Electromyography GLN Murthy, RB Nemani, MS Reddy, MKL Murthy Cognitive Computing Models in Communication Systems, 137 , 2022 2022
A Novel Algorithm for Detecting Spasmodic Dysphonia Voice Pathology using Random Forest Frame Work GLN Murthy, V Iswarya, KR Sri, K Harshitha, C Prasanth 2022 International Conference on Edge Computing and Applications (ICECAA … , 2022 2022 Citations: 3
Blockchain with deep learning-enabled secure healthcare data transmission and diagnostic model S Neelakandan, JR Beulah, L Prathiba, GLN Murthy, EF Irudaya Raj, ... International Journal of Modeling, Simulation, and Scientific Computing 13 … , 2022 2022 Citations: 110
An efficient low complexity compression based optimal homomorphic encryption for secure fiber optic communication D Venu, AVR Mayuri, S Neelakandan, GLN Murthy, N Arulkumar, ... Optik 252, 168545 , 2022 2022 Citations: 86
A two level algorithm for detection of voice pathology using Random Forest with reduced feature dimension DM G.L.Murthy , R.Murali , S.Vijaya Shilpa , Ch.Durga Prasad Turkish Journal of Physiotherapy and Rehabilitation 32 (3), 7109-7115 , 2021 2021
Delineation of putamen from the brain magnetic resonance image for Parkinson disease related applications M Murthy, G.L.N., Mohiddin, S.G., Saida Reddy, B., Imran, Y.M., Durga Prasad ... International Journal of Advanced Science and Technology 29 (3), pp. 3630–3635 , 2020 2020
Detection of rhythm power reduction in alzheimer's disease related disorders G Murthy, G.L.N., Sindhura, C.L., Vara Lakshmi, T., Abhitej, D., Sai Journal of Advanced Research in Dynamical and Control Systems 12 (2), pp … , 2020 2020
MOST CITED SCHOLAR PUBLICATIONS
Blockchain with deep learning-enabled secure healthcare data transmission and diagnostic model S Neelakandan, JR Beulah, L Prathiba, GLN Murthy, EF Irudaya Raj, ... International Journal of Modeling, Simulation, and Scientific Computing 13 … , 2022 2022 Citations: 110
An efficient low complexity compression based optimal homomorphic encryption for secure fiber optic communication D Venu, AVR Mayuri, S Neelakandan, GLN Murthy, N Arulkumar, ... Optik 252, 168545 , 2022 2022 Citations: 86
Deep learning based classification of covid-19 severity using hierarchical deep maxout model MSB Rao, YM Rao, C Venkataiah, GLN Murthy, M Dharani, M Jayamma Biomedical Signal Processing and Control 88, 105653 , 2024 2024 Citations: 10
Improved LSTM-Squeeze net architecture for brain activity detection using EEG with improved feature set SKM Sharif, R Butta, DV Rao, GLN Murthy, NM Devarajan Biomedical Signal Processing and Control 101, 107222 , 2025 2025 Citations: 5
Ensemble deep learning approach for early diagnosis of Alzheimer's disease R Butta, MS Shaik, GLN Murthy Multimedia Tools and Applications 84 (3), 1403-1428 , 2025 2025 Citations: 5
Effective utilization of labeling algorithms for Hippocampus segmentation GLN Murthy, B Anuradha, CSR Krishna, BNK Reddy, JVN Ramesh Eur. J. Sci. Res. 134 (2), 206-211 , 2014 2014 Citations: 5
Isolated word recognition using LPC & vector quantization L Murthy International Journal of Research in Engineering and Technology , 2012 2012 Citations: 5
A machine learning based frame work for classification of neuromuscular disorders GLN Murthy, GP Saii, T Pavani, JL Mohan 2022 IEEE 1st International Conference on Data, Decision and Systems (ICDDS … , 2022 2022 Citations: 4
A Novel Algorithm for Detecting Spasmodic Dysphonia Voice Pathology using Random Forest Frame Work GLN Murthy, V Iswarya, KR Sri, K Harshitha, C Prasanth 2022 International Conference on Edge Computing and Applications (ICECAA … , 2022 2022 Citations: 3
An intelligent multimodal medical image registration using hybrid meta-heuristic optimization with transformer-based residual UNet S Ramakoteswararao, S Palanivel, GLN Murthy Pattern Recognition 172, 112708 , 2026 2026 Citations: 2
A novel machine learning framework: cross transformer based optimization model for the detection and classification of brain tumor using clinical decision analysis AVR Mayuri, SP Maniraj, M Duraisamy, GLN Murthy, K Garg, ... International Journal of Machine Learning and Cybernetics 16 (10), 8331-8358 , 2025 2025 Citations: 2
Alzheimer image registration using hybrid random forest and deep regression network algorithm R Siddabathuni, S Palanivel, GLN Murthy Indonesian Journal of Electrical Engineering and Computer Science 33 (2 … , 2024 2024 Citations: 2
Non Brain Region Removal in Coronal MR images with Histogram Modeling GLN Murthy, B Anuradha International Journal of Software Engineering and Its Applications 10 (12 … , 2016 2016 Citations: 2
Slice specific atlas independent hippocampus segmentation using simple labeling GLN Murthy, B Anuradha, SR Krishna, BNK Reddy, R Sithara 2016 10th International Conference on Intelligent Systems and Control (ISCO … , 2016 2016 Citations: 2
TransDense121-UNet: a multi-scale transformer-based approach for accurate liver tumor segmentation AVR Mayuri, SP Maniraj, M Duraisamy, GLN Murthy, K Garg, ... Evolving Systems 16 (3), 96 , 2025 2025 Citations: 1
Edge Enhanced Fuzzy C Means Algorithm for Hippocampus Segmentation and Abnormality Identification GLN Murthy, B Anuradha Biomedical & Pharmacology Journal 10 (4), 1747 , 2017 2017 Citations: 1
An Euclidean Norm Based Nonlinear Filter for Noise Removal In MR Images GLN Murthy, B Anuradha i-manager's Journal on Image Processing 4 (1), 16 , 2017 2017 Citations: 1
Bias Field Corrected Hippocampus Segmentation using k means Clustering and Region Growing GLN Murthy, B Anuradha International Journal of Hybrid Information Technology 9 (12), 47-54 , 2016 2016 Citations: 1
Error minimization in Brain tissue extraction for T1 weighted MR images GLN Murthy, B Anuradha, M Siva, S Rao, KL Manassa IJIRCCE 3 (5) , 2015 2015 Citations: 1
Detection Of Voice Disorders Using Machine Learning with Data Augmentation GLN Murthy, YL Priya, GV Kumar, KS Kumar 2026 8th International Conference on Devices, Circuits, and Systems (ICDCS), 1-6 , 2026 2026