Dr Loganathan R

@svcengg.edu.in

Professor and Computer Science and Engineering
Sri Venkateshwara College of Engineering

Dr Loganathan R


                  Download Compact PDF  
https://researchid.co/drloganathanr

RESEARCH INTERESTS

Medical Image Compression, Data Mining, Machine Learning, Wireless Sensor Networks
14

Scopus Publications

170

Scholar Citations

8

Scholar h-index

7

Scholar i10-index

Scopus Publications

  • An active learning driven deep spatio-textural acoustic feature ensemble assisted learning environment for violence detection in surveillance videos
    Duba Sriveni, Dr.Loganathan R
    Engineering Science and Technology an International Journal, 2025
    In this paper, a novel and robust deep spatio-textural acoustic feature ensemble-assisted learning environment is proposed for violence detection in surveillance videos (DestaVNet). As the name indicates, the proposed DestaVNet model exploits visual and acoustic features to perform violence detection. Additionally, to ensure the scalability of the solution, it employs an active learning concept that retains optimally sufficient frames for further computation and thus reduces computational costs decisively. More specifically, the DestaVNet model initially splits input surveillance footage into acoustic and video frames, followed by multi-constraints active learning based on the most representative frame selection. It applied the least confidence (LC), entropy margin (EM), and margin sampling (MS) criteria to retain the optimal frames for further feature extraction. The DestaVNet model executes pre-processing and feature extraction separately over the frames and corresponding acoustic signals. It performs intensity equalization, histogram equalization, resizing and z-score normalization as pre-processing task, which is followed by deep spatio-textural feature extraction by using gray level co-occurrence matrix (GLCM), ResNet101 and SqueezeNet deep networks. On the other hand, the different acoustic features, including mel-frequency cepstral coefficient (MFCC), gammatone cepstral coefficient (GTCC), GTCC-Δ, harmonic to noise ratio (HNR), spectral features and pitch were obtained. These acoustic and spatio-textural features were fused to yield a composite audio-visual feature set, which was later processed for principal component analysis (PCA) to minimize redundancy, and k-NN as part of an ensemble classifier to enhance prediction accuracy, achieving superior performance. The z-score normalization was performed to alleviate the over-fitting problem. Finally, the retained feature sets were processed for two-class classification by using a heterogeneous ensemble learning model, embodying SVM, DT, k-NN, NB, and RF classifiers. Simulation results confirmed that the proposed DestaVNet model outperforms other existing violence prediction methods, where its superiority was affirmed in terms of the (99.92%), precision (99.67%), recall (99.29%) and F-Measure (0.992).
  • Drawer Cosine optimization enabled task offloading in fog computing
    Bibi Ameena, Loganthan Ramasamy
    Expert Systems with Applications, 2025
  • Efficient Heuristic Replication Techniques for High Data Availability in Cloud
    H. L. Chandrakala, R. Loganathan
    Computer Systems Science and Engineering, 2023
    Most social networks allow connections amongst many people based on shared interests. Social networks have to offer shared data like videos, photos with minimum latency to the group, which could be challenging as the storage cost has to be minimized and hence entire data replication is not a solution. The replication of data across a network of read-intensive can potentially lead to increased savings in cost and energy and reduce the end-user’s response time. Though simple and adaptive replication strategies exist, the solution is non-deterministic; the replicas of the data need to be optimized to the data usability, performance, and stability of the application systems. To resolve the non-deterministic issue of replication, metaheuristics are applied. In this work, Harmony Search and Tabu Search algorithms are used optimizing the replication process. A novel Harmony-Tabu search is proposed for effective placement and replication of data. Experiments on large datasets show the effectiveness of the proposed technique. It is seen that the bandwidth saving for proposed harmony-Tabu replication performs better in the range of 3.57% to 18.18% for varying number of cloud datacenters when compared to simple replication, Tabu replication and Harmony replication algorithm.
  • Estimating the State of Health of Lithiumion Batteries using Support Vector Regression
    Suhas G K, Ashwini Singh S, Trupthi V, Keerthishree P V, Deepak N R, Loganathan R
    3rd IEEE International Conference on Mobile Networks and Wireless Communications Icmnwc 2023, 2023
    The car business is changing as a result of recent developments in lithium-ion (Li-ion) storage technology. Fully electric cars (EVs) have the greatest range of autonomy and can operate in a variety of driving and environmental conditions. Stated differently, the same State of Charge (SOC) on two similar model EVs does not always equate to the same distance traveled because other factors affect how well the EVs perform, including the driver's style of behavior, the route, and even the State of Health (SOH) of the battery. The ratio of the battery's rated capacity to its current maximum capacity is known as the state of health, or SOH. It is an essential metric for characterizing the level of deterioration in a battery for a fully electric car. It also acts as a critical reference point for assessing the condition of a retired battery and computing its driving range. Support vector regression is used to estimate the state of health (SOH) of lithium-ion batteries, which is essential for their safe and lifetime-optimized operation.
  • Hybrid Neural Approach for Face and Associated Emotion Recognition Using Swarm Intelligence-Based Ensemble Network
    Mrs. Ismath Unnisa, Dr. Loganathan R.
    Indian Journal of Computer Science and Engineering, 2021
    In this work, a hybrid approach which carries the Radial Basis Function Neural Network and Multilayer Perceptron Neural Network have been applied in a cascaded manner to recognize the face and associated emotions. The variability of individual classifier performances has been reduced by providing the ensemble approach. The formation of ensemble has been developed using the intelligent manner with the help of particle swarm optimization. The applied ensemble approach provided the weighted importance of individual entities according to their performances. The proposed ensemble approach has been proven to be useful over the development of ensemble classifier for XOR classification problem. Each face has been carried with a different form of emotion which has been tested and performance was compared against the individual classifier module.
  • Novel AODV based service discovery protocol for MANETS
    Smitha Kurian, Loganathan Ramasamy
    Wireless Networks, 2021
  • Spatial Machines for Heterogeneous MRI Data—A Critical Review
    Zabiha Khan, R. Loganathan
    Lecture Notes in Civil Engineering, 2021
  • Securing service discovery from denial of service attack in mobile ad hoc network (manet)
    Smitha Kurian, Loganathan Ramasamy
    International Journal of Computer Networks and Applications, 2021
    Mobile Ad Hoc networks (MANET) are resource constrained and operate on the basis of mutual cooperation. As a result, service discovery is one of the essential services of MANET. Service discovery was integrated onto Ad Hoc on Demand Distance Vector (AODV) Routing protocol, since service discovery was best performed at the network layer with minimal control messages. But this integration echoes the security threats of AODV protocol onto the service discovery process. The security of AODV protocol has drawn ample attention and various studies and methodologies are proposed. But most of the proposed techniques either address the flooding attack or the black hole attack but addressing both these issues simultaneously has been a challenge. Since the nodes in the network are resource constrained achieving the security objective with minimal overhead is also a target that needs to be achieved. We propose a trust based methodology at the level of individual node, that avoids the denial of service attack by controlling both the packet dropping attack and the flooding attack of the service discovery extended AODV protocol. This scheme assists in the selection of a safe path between the consumer and the server by ensuring that a cooperative node with high trust is selected at every hop. The trust value of the non-cooperative or flooding nodes is decreased and is thus avoided from safe paths. With simulated experiments it is demonstrated that the proposed system has 4% lesser control message overhead, the service discovery ratio improved by 13% and the service discovery latency was also considerably reduced. Index Terms – Service Discovery, AODV, Flooding Attack, Packet Dropping Attack, Denial of Service, Sleep Deprivation.
  • AutoLiv: Automated Liver Tumor Segmentation in CT Images
    Zabiha Khan, R Loganathan
    Proceedings of the International Conference on Smart Technologies in Computing Electrical and Electronics Icstcee 2020, 2020
    Gastrointestinal (GI) cancer consists of a group of ten cancers that affect the various accessory organs of the digestive system and liver cancer is one of them. In India, it is ranked twelfth in terms of new cases, eight in terms of deaths and increasing as per the Global cancer Observatory data of last year. Like other cancers, it can be cured if detected early. But the diagnostic performance of Computerized Tomography (CT) images for Liver cancer is interpreter-dependent and prone to human errors. Medical image segmentation and analysis of tumor can help in Computer-aided diagnosis (CAD). Automatic Segmenting of liver and tumor is a complex task as it depends on the shape, location, texture and intensity. Therefore, to develop a general-purpose algorithm that fits all is not possible. Both these tasks can be performed either manually or in a semi-automated manner. In this paper we present AutoLiv, automated liver-tumor detection in CT images. In the first stage, threshold-based slope difference differentiation (SDD) technique is used for segmentation of liver and using this in the second stage we carry out tumor detection by alternative fuzzy c-means (AFCM) clustering algorithm. MATLAB based results and manual segmentation results are compared. A close correlation is observed between both the manual and automated approach with very high degree of spatial overlap seen in the regions-of-interest (ROIs) isolated by both methods.
  • Human facial emotion recognition using adaptive sigmoidal transfer function in MLP neural network
    Mrs. Ismath Unnisa, , Dr. Loganathan R, and
    International Journal of Engineering and Advanced Technology, 2019
    The human face is very sensitive towards inner feelings particularly with different state of mind under various conditions. The facial expression has used in computer vision to understand the human response against stimuli. But the facial expression is also having the nature of variability and controllability hence its complete generalization from a computer vision point of view is very difficult and challenging, though acceptable performances can be achieved. In this paper, a two stage based facial expression recognition model which carry the Principal component analysis as a feature extractor in the first stage and self-adaptive based activation function in feedforward neural network as a classifier in the second stage have applied. Use of principal component analysis reduces the dimension of features while the adaptive slope of transfer function provides another parameter along with weights to change in making learning faster and accurate. Six most dominant state of facial emotion like angry, surprise, sadness, normal, happy and fear have considered in this paper and performances have been tested over variable expressions. The benefit of the proposed model of self-adaptive activation function has verified through the benchmark XOR problem classification.
  • A harmonized dynamic quality of service aware data replication strategy in cloud
    Chandrakala H L, , Dr. Loganathan R, and
    International Journal of Innovative Technology and Exploring Engineering, 2019
  • Active contour based medical image segmentation and compression using biorthogonal wavelet and embedded zerotree
    Indian Journal of Science and Technology, 2013
  • Medical image compression with lossless region of interest using adaptive active contour
    Loganathan
    Journal of Computer Science, 2012
  • An improved active contour medical image compression technique with lossless region of interest
    R Loganathan, Y.S. Kumaraswamy
    Tisc 2011 Proceedings of the 3rd International Conference on Trendz in Information Sciences and Computing, 2011

RECENT SCHOLAR PUBLICATIONS

  • Enhanced robust image watermarking using advanced wavelet transforms and deep learning-based optimization
    T Jayachandran, GB Mohankumar, S Krithika, S Sivaranjani, SS Kumar, ...
    Information and Communication Systems, 366-369 , 2026
    2026
  • Multi-constraints active learning assisted deep-ensemble spatio-textural feature learning model for violence detection in surveillance dataset
    D Sriveni, L R
    Connection Science 37 (1), 2544539 , 2025
    2025
    Citations: 2
  • An active learning driven deep spatio-textural acoustic feature ensemble assisted learning environment for violence detection in surveillance videos
    D Sriveni, R Loganathan
    Engineering Science and Technology, an International Journal 66, 102050 , 2025
    2025
    Citations: 1
  • Drawer Cosine optimization enabled task offloading in fog computing
    B Ameena, L Ramasamy
    Expert Systems with Applications 259, 125212 , 2025
    2025
    Citations: 10
  • PTFIC - Patient Health Tracking through Fog Enabled Internet of Things Network Using Optimized Classifier
    LR Bibi Ameena
    International Journal of Intelligent Systems and Applications in Engineering … , 2024
    2024
  • Estimating the State of Health of Lithiumion Batteries using Support Vector Regression
    LR Suhas G K, Ashwini Singh S, Trupthi V, Keerthishree P V, Deepak N R
    IEEE 3rd International Conference on Mobile Networks and Wireless … , 2024
    2024
  • Efficient Heuristic Replication Techniques for High Data Availability in Cloud
    HL Chandrakala, R Loganathan
    Computer Systems Science and Engineering 45 (3), 3151-3164 , 2023
    2023
    Citations: 3
  • Transfer learning based classification of MSI and MSS gastrointestinal cancer
    Z Khan, R Loganathan
    International journal of health sciences 6 (S1), 1857-1872 , 2022
    2022
    Citations: 4
  • Novel AODV based service discovery protocol for MANETS
    S Kurian, L Ramasamy
    Wireless Networks 27 (4), 2497-2508 , 2021
    2021
    Citations: 20
  • Securing Service Discovery from Denial of Service Attack in Mobile Ad Hoc Network (MANET
    S Kurian
    International Journal of Computer Networks and Applications (IJCNA) , 2021
    2021
    Citations: 12
  • Spatial Machines for Heterogeneous MRI Data—A Critical Review
    Z Khan, R Loganathan
    Smart Technologies for Sustainable Development: Select Proceedings of SMTS … , 2020
    2020
  • AutoLiv: Automated liver tumor segmentation in CT images
    Z Khan, R Loganathan
    2020 International Conference on Smart Technologies in Computing, Electrical … , 2020
    2020
    Citations: 8
  • Eye Blinks to Voice
    S Khanum, S Zaiba, N Asma, R Loganathan
    International Scientific Journal of Contemporary Research in Engineering … , 2020
    2020
  • A Survey on Prober: An automated network vulnerability scanner.
    R Loganathan, FA Khan, I Gulzar, IN Parray, FA Bhat
    International Scientific Journal of Contemporary Research in Engineering … , 2020
    2020
    Citations: 3
  • Radiomics in Prostate MRI: A Review on Opportunities & Challenges
    Z Khan
    International Scientific Journal of Contemporary Research in Engineering … , 2020
    2020
    Citations: 3
  • A Survey on Paperless Examination
    R Loganathan, BB Aliya, SSU Rehman, A Pasha
    International Scientific Journal of Contemporary Research in Engineering … , 2020
    2020
    Citations: 3
  • Automated Allocation of Resources for Examination System using Genetic Algorithm
    L R, S Kurian
    International Journal of Engineering and Advanced Technology 9 (2), 1052-1055 , 2019
    2019
  • AODV based Service Discovery Protocol with Two Hop Neighbor Information
    LR Smitha Kurian
    International Journal of Recent Technology and Engineering 8 (4), 4068-4072 , 2019
    2019
  • Human Facial Emotion Recognition using Adaptive Sigmoidal Transfer Function in MLP Neural Network
    I Unnisa, L R
    International Journal of Engineering and Advanced Technology 9 (1), 4103-4113 , 2019
    2019
  • A Harmonized Dynamic Quality of Service Aware Data Replication Strategy in Cloud
    LR Chandrakala H L
    International Journal of Innovative Technology and Exploring Engineering 8 … , 2019
    2019

MOST CITED SCHOLAR PUBLICATIONS

  • Feature reduction using principal component analysis for opinion mining
    J Jotheeswaran, R Loganathan, B Madhu Sudhanan
    International Journal of Computer Science and Telecommunications 3 (5), 118-121 , 2012
    2012
    Citations: 27
  • Active contour based medical image segmentation and compression using biorthogonal wavelet and embedded zerotree
    L R, K Y S
    Indian J. Sci. Technol 6, 4390-4395 , 2013
    2013
    Citations: 23
  • Novel AODV based service discovery protocol for MANETS
    S Kurian, L Ramasamy
    Wireless Networks 27 (4), 2497-2508 , 2021
    2021
    Citations: 20
  • An improved active contour medical image compression technique with lossless region of interest
    R Loganathan, YS Kumaraswamy
    3rd International conference on trendz in information sciences & computing … , 2011
    2011
    Citations: 19
  • Medical image compression using biorthogonal spline wavelet with different decomposition
    R Loganathan, YS Kumaraswamy
    IJCSE International Journal on Computer Science and Engineering 2 (9), 3003-3006 , 2010
    2010
    Citations: 14
  • Securing Service Discovery from Denial of Service Attack in Mobile Ad Hoc Network (MANET
    S Kurian
    International Journal of Computer Networks and Applications (IJCNA) , 2021
    2021
    Citations: 12
  • Drawer Cosine optimization enabled task offloading in fog computing
    B Ameena, L Ramasamy
    Expert Systems with Applications 259, 125212 , 2025
    2025
    Citations: 10
  • AutoLiv: Automated liver tumor segmentation in CT images
    Z Khan, R Loganathan
    2020 International Conference on Smart Technologies in Computing, Electrical … , 2020
    2020
    Citations: 8
  • Medical image compression with lossless region of interest using adaptive active contour
    R Loganathan, YS Kumaraswamy
    Journal of Computer Science 8 (5), 747 , 2012
    2012
    Citations: 8
  • PERFORMANCE EVALUATION OF IMAGE COMPRESSION FOR MEDICAL IMAGE
    R Loganathan, YS Kumaraswamy
    Indian Journal of Computer Science and Engineering 1 (4), 138-143 , 2013
    2013
    Citations: 6
  • Transfer learning based classification of MSI and MSS gastrointestinal cancer
    Z Khan, R Loganathan
    International journal of health sciences 6 (S1), 1857-1872 , 2022
    2022
    Citations: 4
  • Medical Image Compression with Lossless Region of Interest Using Fuzzy Adaptive Active Contour
    R Loganathan, YS Kumaraswamy
    International Conference on Computational Techniques and Mobile Computing … , 2012
    2012
    Citations: 4
  • Efficient Heuristic Replication Techniques for High Data Availability in Cloud
    HL Chandrakala, R Loganathan
    Computer Systems Science and Engineering 45 (3), 3151-3164 , 2023
    2023
    Citations: 3
  • A Survey on Prober: An automated network vulnerability scanner.
    R Loganathan, FA Khan, I Gulzar, IN Parray, FA Bhat
    International Scientific Journal of Contemporary Research in Engineering … , 2020
    2020
    Citations: 3
  • Radiomics in Prostate MRI: A Review on Opportunities & Challenges
    Z Khan
    International Scientific Journal of Contemporary Research in Engineering … , 2020
    2020
    Citations: 3
  • A Survey on Paperless Examination
    R Loganathan, BB Aliya, SSU Rehman, A Pasha
    International Scientific Journal of Contemporary Research in Engineering … , 2020
    2020
    Citations: 3
  • Multi-constraints active learning assisted deep-ensemble spatio-textural feature learning model for violence detection in surveillance dataset
    D Sriveni, L R
    Connection Science 37 (1), 2544539 , 2025
    2025
    Citations: 2
  • An active learning driven deep spatio-textural acoustic feature ensemble assisted learning environment for violence detection in surveillance videos
    D Sriveni, R Loganathan
    Engineering Science and Technology, an International Journal 66, 102050 , 2025
    2025
    Citations: 1
  • Enhanced robust image watermarking using advanced wavelet transforms and deep learning-based optimization
    T Jayachandran, GB Mohankumar, S Krithika, S Sivaranjani, SS Kumar, ...
    Information and Communication Systems, 366-369 , 2026
    2026
  • PTFIC - Patient Health Tracking through Fog Enabled Internet of Things Network Using Optimized Classifier
    LR Bibi Ameena
    International Journal of Intelligent Systems and Applications in Engineering … , 2024
    2024