SIVA SATYA SREEDHAR P

@gecgudlavalleru.ac.in

Assistant Professor and Information Technology
Gudlavalleru Engineering College

SIVA SATYA SREEDHAR P


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https://researchid.co/psssreedhar

RESEARCH INTERESTS

Image Processing, Machine Learning, Deep Learning, Artificial Intelligence
29

Scopus Publications

312

Scholar Citations

8

Scholar h-index

7

Scholar i10-index

Scopus Publications

  • Video anomaly segmentation and classification using a novel multi-scale convolutional three-dimensional Geysar-inspired information aggregation model
    K. Ashok Reddy, P. Siva Satya Sreedhar, M. Vamsi Krishna, Melam Nagaraju, Balaji Tedla
    Neurocomputing, 2026
  • Swertiamarin Attenuates Acrylamide-Induced Neurotoxicity in Zebrafish: Imaging and Mechanistic Insights Via Nrf-2/HO-1 Signalling Pathway
    Monita Wahengbam, Siva Satya Sreedhar P, C. Priya, Sundhar Singh Pitta, S. Navaneethan, S. Nithyanandh, S. Divyapriya
    Journal of Pharmaceutical Innovation, 2026
  • An Efficient Web-Based System for Accreditation-Oriented Faculty Data Management
    Mohammad Salma Sulthana, Mude Varsha, Mokara Harsha Vardhan, Jampana Manideep, Siva Satya Sreedhar P
    Proceedings Icses 2026 5th International Conference on Innovative Computing Intelligent Communication and Smart Electrical Systems, 2026
    The accreditation tasks in higher education need faculty academic data that is accurate, structured, and easily retrievable, but the traditional documentation activities cause inefficiencies, inconsistency of data, and great administrative effort. To resolve this, an effective web-based accreditation-oriented faculty data management system is offered. The system uses mathematical data, formalization, validation based on metadata, role-based access control, hierarchical indexing, and time analytics to centralize records. The metadata validation accuracy of the performance evaluation is 98.6 %, the time of retrieving the evidence is 0.42 s, and the accreditation report generation time is 2.6 min. The administrative workload is decreased by 64.3 %, and a departmental compliance score is 0.91, as well as storage utilization efficiency is 0.78. Compared to existing systems, the high accreditation preparedness and reduced manual dependency are higher. These outcomes prove that the proposed platform is efficient in increasing audit preparedness, operational efficiency, and scalable academic data governance.
  • Music interventions and obstructive sleep apnea: a brain connectivity analysis
    J. Rajeswari, S. Navaneethan, P. Siva Satya Sreedhar, M. Jagannath
    Biomedical Engineering Online, 2025
    BACKGROUND: The blockage in the upper airway that occurs, while sleeping is represented as obstructive sleep apnea (OSA). This seem to be a major issue which cause breathing difficulties also increases the risk of severe complications, such as heart attacks and strokes. Therefore, in this proposed study the impact of OSA using brain connectivity analysis under various conditions such as Neelambari, Kapi, and no music has been investigated. The electroencephalogram (EEG) recordings of twelve subjects were acquired in two different conditions, such as listening to music 1 and 2 (Neelambari and Kapi) and the absence of music. The raw EEG signals were then pre-processed using both bandpass and notch filters. Meanwhile, the EEG sub-bands were obtained using the wavelet packet decomposition (WPD) method. These sub-bands, including delta, theta, alpha, and beta, were used for brain connectivity analysis. This approach provides the visualization of frequency-specific regional brain connectivity patterns by applying Pearson Correlation to the absolute values of the detail coefficients from WPD using a graph theory metric, node strength. RESULTS: Increased connectivity in the right hemisphere of the brain was observed among the nodes in the frontal and temporal regions (F8, FC6, and T8) when participants listened to Neelambari music (Music 1). In the beta band, the correlation values for Neelambari music ranged from a minimum of 0.943 to a maximum of 0.998. In the delta band, positive correlation values ranged from 0.945 (minimum) to 0.999 (maximum). The alpha and theta bands exhibited moderate correlations, ranging from 0.746 (minimum) to 0.996 (maximum). Compared to Kapi music, Neelambari music showed stronger neural synchronization, evidenced by consistently higher correlation values across all frequency bands. This increased connectivity suggests that Neelambari music may profoundly impact brain dynamics, potentially enhancing cognitive or physiological responses. CONCLUSIONS: In conclusion, it has been analyzed that OSA patients have positive brain connectivity while listening to music 1 (Neelambari).
  • Optimizing Energy-Efficient Task Offloading in Edge Computing: A Hybrid AI-Based Approach
    Anwar Ahamed Shaikh, I. Carol, Meenakshi, Helina Rajini Suresh, M. Thillai Rani, J. Rejina Parvin
    International Journal of Computational and Experimental Science and Engineering, 2025
    Edge computing has emerged as a pivotal technology for managing computational workloads in latency-sensitive applications by offloading tasks from resource-constrained Internet of Things (IoT) devices to nearby edge servers. However, optimizing task offloading while ensuring energy efficiency remains a significant challenge. This paper proposes a Hybrid AI-Based Task Offloading (HATO) model, integrating Reinforcement Learning (RL) with Deep Neural Networks (DNNs) to dynamically allocate computational resources while minimizing energy consumption. The HATO framework formulates task offloading as a multi-objective optimization problem, considering factors such as device workload, network latency, edge server availability, and energy constraints.Experimental evaluations demonstrate that the proposed model achieves a 27.3% reduction in energy consumption, a 19.6% improvement in task completion time, and a 31.2% enhancement in overall edge server utilization compared to conventional heuristic-based methods. The reinforcement learning module adapts task offloading strategies in real-time, ensuring optimal computational load balancing while minimizing latency. The proposed Hybrid AI-Based Approach outperforms baseline models in diverse edge computing scenarios, making it a scalable and efficient solution for next-generation IoT applications.
  • Machine Learning-Integrated Air Quality and Environmental Monitoring Processes
    V. Sujay, P. Siva Satya Sreedhar, Harshada Bhushan Magar, S. C. Shamkuwar, T. Pravin
    Enhancing Data Driven Electronics Through Iot, 2025
    This chapter examines the collaboration between machine learning and remote sensing technology to improve air quality and environmental monitoring. It applies advanced techniques and extensive datasets to examine, forecast, and manage environmental elements in real time. The chapter explores the significance of monitoring air quality and the environment for public health and sustainable development. It explains the fundamentals of remote sensing and machine learning and how they can join forces. This research delves into how satellite imagery, sensor networks, and data fusion methods can provide a comprehensive view of the environment. It investigates their successful applications in various regions with diverse climates. The chapter highlights the challenges in this field such as obtaining quality data, addressing intensive computational requirements, and fostering interdisciplinary collaboration. It also outlines future directions and emerging opportunities, with a focus on promising technologies like deep learning and cloud computing.
  • Cryptography and Steganography for Data Hiding in Images: A Novel Architecture and Implementation
    Satya Phani Krishna Sastry Jonnalagadda, Shanmukhi Achanta, Sai Praneeth Arava, Venkata Ganesh Avvaru, Siva Satya Sreedhar P
    Proceedings 1st International Conference on Frontier Technologies and Solutions Icfts 2025, 2025
    The proposed system presents safe data concealment and communication by combining compression, steganography, and cryptography. It ensures data confidentiality and integrity through the encryption module, implemented using AES-256-CBC. Dynamic least significant bit (LSB) steganographic techniques allow for an undetectable method with PSNR values higher than 55 dB and SSIM scores greater than 0.99. The best outcomes are: with the lossless DEFLATE compression, the embedding efficiency improved, and average payload size is reduced by 41.23%. The modular structure used in Flask makes it suitable for real time applications, mainly because it has scalability and smooth integration features. The experimental results depict a general system accuracy of 99.98% with negligible computing overhead, thereby proving its reliability and feasibility. Security, imperceptibility, and performance all reveal it to be much superior to the present techniques. Although safe data concealing is a major concern, the approach recommended here offers a flexible solution that suits the situation.
  • Weapon Detection Using Region-Based Convolutional Neural Network (RCNN)
    Jyothirmayi Desu, Venkata Abhishek Chigulla, Karthik Sai Chittibomma, Mounika Ayinapuru, Siva Satya Sreedhar P
    Proceedings 1st International Conference on Frontier Technologies and Solutions Icfts 2025, 2025
    Automatic weapon detection in surveillance systems, increasing the safety of public areas. In this work, a deep-learningdetection method is presentedthat focuses on real-time performance. A multi-task loss function is used and an enhanced CNN architecture that improves the accuracy of localization and classification in our system. On a dataset of 50,000 images, the model shows excellent performance with a 99.38% IoU, 99.51% recall, 99.32% precision, and 99.47% accuracy. The model surpasses all the state-of-the-art methods, including SSD, YOLOv5, and Faster R-CNN, in terms of perseverance, inference speed, and detection accuracy. Its processing speed ensures real-time implementation of the system in surveillance scenarios as 158.64 FPS. Comparing the proposed system with others clearly shows the efficiency of the system in the management of diverse types of weapons with minimal false positives. These results set up a benchmark for real-time weapons detection with a high degree of accuracy, answering significant security issues
  • Design and Implementation of an IoT-Based Real-Time Monitoring System for Ground Vibration in Opencast Mines in Civil Infrastructure
    S. Kannan, V. Sujay, P. Siva Satya Sreedhar, Tedla Balaji, Maduri V. N. S. S. R. K. Sai Somayajulu, Sarojarani Polamarasetti
    Sustainable Civil Infrastructures, 2025
  • A deep learning approach for lung cancer classification and nodule identification using CT-images
    Siva Satya Sreedhar Purilla, Ashok Reddy Kandula, Kandula Srikanth, Jonnalagadda V.N. Raju, Tedla Balaji, Sureshbabu Chandanapalli
    International Journal of Ad Hoc and Ubiquitous Computing, 2025
    This work devises an efficient technique deep learning enabled hybrid Shepard convolutional Kronecker network (ShCKN) for lung cancer classification and nodule identification using computed tomography (CT)-images. Initially, the image input is taken from the specific database and the acquired images are fed into an image pre-processing unit, where the Laplacian filter removes unnecessary noise. Thereafter, segmentation of the lung lobe is performed using K-Net. Then, nodules are detected using grid-based schemes. After that, feature extraction is performed and essential features are extracted using entropy measures. Finally, lung cancer classification is accomplished by the devised ShCKN, which is obtained by combining Shepard convolutional neural networks (ShCNN) and deep kernel networks (DKN). The performance estimation of ShCKN is validated based on early devised approaches and performance measures; the ShCKN achieves accuracy, F-measure, precision, recall, and specificity at 92%, 92%, 91%, 94%, and 93%.
  • Impacts of 5G machine learning techniques on telemedicine and social media professional connection in healthcare
    P. Siva Satya Sreedhar, V. Sujay, Maderametla Roja Rani, L. Melita, S. Reshma, Sampath Boopathi
    Analyzing Current Digital Healthcare Trends Using Social Networks, 2024
  • Cloud IoT Based Surveillance System for Tracking and Monitoring of Domestic Animals
    Ande NagaSai Manikanta, Abdul Farid Baba, Devarakonda Srivalli Vyshnavi, Dondapati Kiran Paul, Siva Satya Sreedhar P
    2nd International Conference on Integrated Circuits and Communication Systems Icicacs 2024, 2024
  • Intelligent Helmet for Coal Miners Monitoring System using LORA Technology and Machine Learning
    Morampudi Anu Sri, P Siva Satya Sreedhar, Maddhali Rudra Sai Naga Venkata Sanjay Gupta, Kunduru Anirudh Ram Naga Sri Sreyesh, Kundeti Chandhini
    10th International Conference on Advanced Computing and Communication Systems Icaccs 2024, 2024
  • Energy Efficient Task Scheduling Strategy using Modified Coot Optimization Algorithm for Cloud Computing
    Kandan Kandan, , , , , , M. Mutharasu, Siva Satya Sreedhar. P., S. Thenappan, G. Nagarajan
    Journal of Intelligent Systems and Internet of Things, 2024
  • Soil-Based Crop Recommendation System Using Machine Learning
    Kristuboyina Abhinov, Kornepati Sai Saranya, Mannem Mahendra, Ch Suresh Babu, Siva Satya Sreedhar P
    2024 International Conference on Advances in Data Engineering and Intelligent Computing Systems Adics 2024, 2024
  • Optimizing Energy Efficiency in Electric Vehicles Through Fuzzy Logic and Neural Network Algorithms
    M Devi, Siva Satya Sreedhar P, S. Geetha Priya, M. Amutha, D. Kanagajothi, R.Kalaivani Sri
    International Conference on Distributed Computing and Optimization Techniques Icdcot 2024, 2024
  • Revolutionizing User Experience for Product Quality Evaluation using AR/VR and NLP
    Bande Bhavya Sri, Kadamati Dharani Naga Sai Amulya, Beulah Pallapothu, M.V.L.N. Raja Rao, Siva Satya Sreedhar P, A. Abirami
    International Conference on Distributed Computing and Optimization Techniques Icdcot 2024, 2024
  • Enhancing Hyperparameters for Improved Flight Delay Prediction Using Machine Learning Algorithms
    V. Sujay, S Lalitha, Siva Satya Sreedhar P, Habeeb Omotunde, S. Vijaya, K. Prasanna Mery
    2nd International Conference on Integrated Circuits and Communication Systems Icicacs 2024, 2024
  • Hybrid CNN-LSTM Machine Learning Algorithm for Driver Distraction Detection
    Sri Raman Kothuri, V. Sujay, Siva Satya Sreedhar P, Prachi Juyal, Jyothi Prasad M, R Bhuvaneshwari
    2nd International Conference on Integrated Circuits and Communication Systems Icicacs 2024, 2024
  • Enhanced Jaya Optimization Algorithm with Deep Learning Assisted Oral Cancer Diagnosis on IoT Healthcare Systems
    R. Rajkumar, , , , , , , , , Dınesh Valluru, Siva Satya Sreedhar. .., N. Ramshankar, Sujatha. .., Somasundaram. R., M. Sudha, S. Navaneethan
    Journal of Intelligent Systems and Internet of Things, 2024
  • Automated EEG based Emotion Detection using Bonobo Optimizer with Deep Learning on Human Computer Interaction
    M. M., , , , , , , , , M. S. Minu, P. Vidyasri, Habeeb Omotunde, A. Tamizharasi, R. Logarasu, Rama Prabha K.. P., V. Subashree
    Journal of Intelligent Systems and Internet of Things, 2024
  • Gray wolf optimization and image enhancement with NLM Algorithm for multimodal medical fusion imaging system
    S. Rajakumar, P. Siva Satya Sreedhar, S. Kamatchi, G. Tamilmani
    Biomedical Signal Processing and Control, 2023
  • Crime Detection Using a Technique of Deep Learning
    Meduri V. N. S. S. R. K. Sai Somayajului, Balaji Tedla, P. Siva Satya Sreedhar
    Cognitive Science and Technology, 2023
  • The Human Eye Pupil Detection System Using BAT Optimized Deep Learning Architecture
    S. Navaneethan, P. Siva Satya Sreedhar, S. Padmakala, C. Senthilkumar
    Computer Systems Science and Engineering, 2023
  • Phishing Attack Detection Using Convolutional Neural Networks
    Siva Satya Sreedhar P, Sravani Velpula, Rishwitha Parise, Naidu Krishna Vamsi, Sakhamuri Krishna Chaitanya
    2023 9th International Conference on Advanced Computing and Communication Systems Icaccs 2023, 2023
  • An Efficient Class Room Teaching Learning Method Using Augmented Reality
    Dinesh Valluru, Mohammed Ahmed Mustafa, Hind Yasin Jasim, Kandula Srikanth, M.V.L.N. RajaRao, Purilla Siva Satya Sreedhar
    2023 9th International Conference on Advanced Computing and Communication Systems Icaccs 2023, 2023
  • Classification similarity network model for image fusion using resnet50 and googlenet
    P. Siva Satya Sreedhar, N. Nandhagopal
    Intelligent Automation and Soft Computing, 2022
  • Double OptconNet architecture based facial expression recognition in video processing
    Melam Nagaraju, Adilakshmi Yannam, Siva Satya Sreedhar P, Maridu Bhargavi
    Imaging Science Journal, 2022
  • Energy Conservation for Environment Monitoring System in an IoT based WSN
    Siva Satya Sreedhar, R Anitha, Priya Rachel, S Suganya, C Ramesh Babu Durai, G S Uthayakumar
    Proceedings 2nd International Conference on Smart Technologies Communication and Robotics 2022 Stcr 2022, 2022

RECENT SCHOLAR PUBLICATIONS

  • Swertiamarin Attenuates Acrylamide-Induced Neurotoxicity in Zebrafish: Imaging and Mechanistic Insights Via Nrf-2/HO-1 Signalling Pathway
    M Wahengbam, SS Sreedhar P, C Priya, SS Pitta, S Navaneethan, ...
    Journal of Pharmaceutical Innovation 21 (1), 58 , 2026
    2026
  • Video Anomaly Segmentation and Classification using a Novel Multi-Scale Convolutional Three-Dimensional Geysar-Inspired Information Aggregation Model
    KA Reddy, PSS Sreedhar, MV Krishna, M Nagaraju, B Tedla
    Neurocomputing, 132431 , 2025
    2025
  • System for Ground Vibration in Opencast Mines in Civil Infrastructure
    S Kannan, V Sujay, PSS Sreedhar, T Balaji, MVS Somayajulu, ...
    Recent Advances in Applied Sciences: Engineering and Technology Innovations, 367 , 2025
    2025
  • Music interventions and obstructive sleep apnea: a brain connectivity analysis
    J Rajeswari, S Navaneethan, PSS Sreedhar, M Jagannath
    BioMedical Engineering OnLine 24 (1), 45 , 2025
    2025
    Citations: 5
  • A deep learning approach for lung cancer classification and nodule identification using CT-images
    SSS Purilla, AR Kandula, K Srikanth, JVN Raju, T Balaji, S Chandanapalli
    International Journal of Ad Hoc and Ubiquitous Computing 49 (4), 233-250 , 2025
    2025
  • Machine Learning-Integrated Air Quality and Environmental Monitoring Processes
    V Sujay, PSS Sreedhar, HB Magar, SC Shamkuwar, T Pravin
    Enhancing Data-Driven Electronics Through IoT, 487-514 , 2025
    2025
  • Automated EEG based Emotion Detection using Bonobo Optimizer with Deep Learning on Human Computer Interaction.
    P Sreedhar, S Satya, MS Minu, P Vidyasri, H Omotunde, A Tamizharasi, ...
    Journal of Intelligent Systems & Internet of Things 12 (1) , 2024
    2024
    Citations: 4
  • Design and Implementation of an IoT-Based Real-Time Monitoring System for Ground Vibration in Opencast Mines in Civil Infrastructure
    S Kannan, V Sujay, P Siva Satya Sreedhar, T Balaji, MV Sai Somayajulu, ...
    International Conference on Innovative Discoveries and Emerging Advancements … , 2024
    2024
  • Soil-Based Crop Recommendation System Using Machine Learning
    K Abhinov, KS Saranya, M Mahendra, CS Babu, SS Sreedhar P
    2024 International Conference on Advances in Data Engineering and … , 2024
    2024
    Citations: 7
  • Optimizing Energy Efficiency in Electric Vehicles Through Fuzzy Logic and Neural Network Algorithms
    M Devi, SG Siva Satya Sreedhar P, Priya, M Amutha, D Kanagajothi, ...
    2024 International Conference on Distributed Computing and Optimization … , 2024
    2024
    Citations: 2
  • Revolutionizing User Experience for Product Quality Evaluation using AR/VR and NLP
    BB Sri, KDNS Amulya, B Pallapothu, MR Rao, SS Sreedhar P, A Abirami
    2024 International Conference on Distributed Computing and Optimization … , 2024
    2024
  • Intelligent Helmet for Coal Miners Monitoring System using LORA Technology and Machine Learning
    MA Sri, PSS Sreedhar, MRSNV Sanjay, KARNS Sreyesh, K Chandhini
    2024 10th International Conference on Advanced Computing and Communication … , 2024
    2024
    Citations: 1
  • Energy Efficient Task Scheduling Strategy using Modified Coot Optimization Algorithm for Cloud Computing
    SS Sreedhar P, M Kandan, M Mutharasu, S Thenappan, G Nagarajan
    Full Length Article 12 (1), 45-5-56 , 2024
    2024
  • Cloud IoT Based Surveillance System for Tracking and Monitoring of Domestic Animals
    ANS Manikanta, AF Baba, DS Vyshnavi, DK Paul, CITBSSTMD Animals
    2024 International Conference on Integrated Circuits and Communication … , 2024
    2024
    Citations: 8
  • Enhancing Hyperparameters for Improved Flight Delay Prediction Using Machine Learning Algorithms
    V Sujay, SS Sreedhar P, S Lalitha, H Omotunde, S Vijaya, KP Mery
    2024 International Conference on Integrated Circuits and Communication … , 2024
    2024
    Citations: 3
  • Hybrid CNN-LSTM Machine Learning Algorithm for Driver Distraction Detection
    SR Kothuri, V Sujay, SS Sreedhar P, P Juyal, R Bhuvaneshwari
    2024 International Conference on Integrated Circuits and Communication … , 2024
    2024
    Citations: 7
  • Enhanced Jaya Optimization Algorithm with Deep Learning Assisted Oral Cancer Diagnosis on IoT Healthcare Systems
    R Rajkumar, D Valluru, N Siva Satya Sreedhar P, Ramshankar, S Sujatha, ...
    Journal of Intelligent Systems and Internet of Things 11 (2), 97-7-110 , 2024
    2024
    Citations: 28
  • Impacts of 5G machine learning techniques on telemedicine and social media professional connection in healthcare
    PSS Sreedhar, V Sujay, MR Rani, L Melita, S Reshma, S Boopathi
    Analyzing current digital healthcare trends using social networks, 209-234 , 2024
    2024
    Citations: 47
  • AI BASED DRIVER DROWSINESS DETECTING DEVICE
    MKS Dr.Vengatampalli Sujay, Mr. Ashok Reddy Kandula, Dr. Siva Satya Sreedhar ...
    EP Patent 6,304,504 , 2023
    2023
  • Gray wolf optimization and image enhancement with NLM Algorithm for multimodal medical fusion imaging system
    S Rajakumar, PSS Sreedhar, S Kamatchi, G Tamilmani
    Biomedical Signal Processing and Control 85, 104950 , 2023
    2023
    Citations: 30

MOST CITED SCHOLAR PUBLICATIONS

  • The Human Eye Pupil Detection System Using BAT Optimized Deep Learning Architecture.
    S Navaneethan, PSS Sreedhar, S Padmakala, C Senthilkumar
    Comput. Syst. Sci. Eng. 46 (1), 125-135 , 2023
    2023
    Citations: 90
  • Impacts of 5G machine learning techniques on telemedicine and social media professional connection in healthcare
    PSS Sreedhar, V Sujay, MR Rani, L Melita, S Reshma, S Boopathi
    Analyzing current digital healthcare trends using social networks, 209-234 , 2024
    2024
    Citations: 47
  • Classification Similarity Network Model for Image Fusion Using Resnet50 and GoogLeNet.
    PS Satya Sreedhar, N Nandhagopal
    Intelligent Automation & Soft Computing 31 (3) , 2022
    2022
    Citations: 32
  • Gray wolf optimization and image enhancement with NLM Algorithm for multimodal medical fusion imaging system
    S Rajakumar, PSS Sreedhar, S Kamatchi, G Tamilmani
    Biomedical Signal Processing and Control 85, 104950 , 2023
    2023
    Citations: 30
  • Enhanced Jaya Optimization Algorithm with Deep Learning Assisted Oral Cancer Diagnosis on IoT Healthcare Systems
    R Rajkumar, D Valluru, N Siva Satya Sreedhar P, Ramshankar, S Sujatha, ...
    Journal of Intelligent Systems and Internet of Things 11 (2), 97-7-110 , 2024
    2024
    Citations: 28
  • Deep Neural Network for Image Recognition In Medical Diagnosis.
    AR Siva Satya Sreedhar P,Kandula, K Tamilarasi, S Maan
    Journal of Pharmaceutical Negative Results 13, 386–398. , 2022
    2022
    Citations: 19
  • An Efficient Class Room Teaching Learning Method Using Augmented Reality
    D Valluru, MA Mustafa, HY Jasim, K Srikanth, M RajaRao, PSS Sreedhar
    2023 9th International Conference on Advanced Computing and Communication … , 2023
    2023
    Citations: 15
  • Cloud IoT Based Surveillance System for Tracking and Monitoring of Domestic Animals
    ANS Manikanta, AF Baba, DS Vyshnavi, DK Paul, CITBSSTMD Animals
    2024 International Conference on Integrated Circuits and Communication … , 2024
    2024
    Citations: 8
  • Soil-Based Crop Recommendation System Using Machine Learning
    K Abhinov, KS Saranya, M Mahendra, CS Babu, SS Sreedhar P
    2024 International Conference on Advances in Data Engineering and … , 2024
    2024
    Citations: 7
  • Hybrid CNN-LSTM Machine Learning Algorithm for Driver Distraction Detection
    SR Kothuri, V Sujay, SS Sreedhar P, P Juyal, R Bhuvaneshwari
    2024 International Conference on Integrated Circuits and Communication … , 2024
    2024
    Citations: 7
  • Music interventions and obstructive sleep apnea: a brain connectivity analysis
    J Rajeswari, S Navaneethan, PSS Sreedhar, M Jagannath
    BioMedical Engineering OnLine 24 (1), 45 , 2025
    2025
    Citations: 5
  • Double OptconNet architecture based facial expression recognition in video processing
    M Nagaraju, A Yannam, SS Sreedhar P, M Bhargavi
    The Imaging Science Journal 70 (1), 46-60 , 2023
    2023
    Citations: 5
  • Automated EEG based Emotion Detection using Bonobo Optimizer with Deep Learning on Human Computer Interaction.
    P Sreedhar, S Satya, MS Minu, P Vidyasri, H Omotunde, A Tamizharasi, ...
    Journal of Intelligent Systems & Internet of Things 12 (1) , 2024
    2024
    Citations: 4
  • Enhancing Hyperparameters for Improved Flight Delay Prediction Using Machine Learning Algorithms
    V Sujay, SS Sreedhar P, S Lalitha, H Omotunde, S Vijaya, KP Mery
    2024 International Conference on Integrated Circuits and Communication … , 2024
    2024
    Citations: 3
  • Retracted: Phishing Attack Detection Using Convolutional Neural Networks
    S Velpula, R Parise, NK Vamsi, SK Chaitanya
    2023 9th International Conference on Advanced Computing and Communication … , 2023
    2023
    Citations: 3
  • Energy conservation for environment monitoring system in an IoT based WSN
    SS Sreedhar, R Anitha, P Rachel, S Suganya, CRB Durai, ...
    2022 Smart Technologies, Communication and Robotics (STCR), 1-5 , 2022
    2022
    Citations: 3
  • Optimizing Energy Efficiency in Electric Vehicles Through Fuzzy Logic and Neural Network Algorithms
    M Devi, SG Siva Satya Sreedhar P, Priya, M Amutha, D Kanagajothi, ...
    2024 International Conference on Distributed Computing and Optimization … , 2024
    2024
    Citations: 2
  • Image fusion-the pioneering technique for real-time image processing applications
    P Sreedhar, N Nandhagopal
    Journal of Computational and Theoretical Nanoscience 18 (4), 1208-1212 , 2021
    2021
    Citations: 2
  • Intelligent Helmet for Coal Miners Monitoring System using LORA Technology and Machine Learning
    MA Sri, PSS Sreedhar, MRSNV Sanjay, KARNS Sreyesh, K Chandhini
    2024 10th International Conference on Advanced Computing and Communication … , 2024
    2024
    Citations: 1
  • A novel approach for discovering relevant semantic associations on social Web mining
    LP Maguluri, MV Krishna, PSS Sridhar
    2014 Conference on IT in Business, Industry and Government (CSIBIG), 1-7 , 2014
    2014
    Citations: 1