M. Rajasekaran

发表

Acute Cyanide Poisoning: Identification of Prussic Acid in by Analyzing of Various Parameters in Cattle

M. P. Rajasekaran, V. Govindaraj, P. Sowmiya, 2020, 2020 International Conference on Communication and Signal Processing (ICCSP).

Multiscale Laplacian graph kernel features combined with tree deep convolutional neural network for the detection of ECG arrhythmia

M. Ramkumar, M. Rajasekaran, A. Lakshmi, 2022, Biomed. Signal Process. Control..

A biologically-inspired hybrid deep learning approach for brain tumor classification from magnetic resonance imaging using improved gabor wavelet transform and Elmann-BiLSTM network

M. P. Rajasekaran, V. Govindaraj, T. Arunprasath, 2022, Biomed. Signal Process. Control..

A Review on Magnetic Resonance Spectroscopy for Clinical Diagnosis of Brain Tumour using Deep Learning

M. Rajasekaran, A. Al Bimani, S. K. Rajeev, 2021, 2021 3rd International Conference on Advances in Computing, Communication Control and Networking (ICAC3N).

Automatic segmentation of gallbladder using bio-inspired algorithm based on a spider web construction model

V. Muneeswaran, M. Rajasekaran, 2018, The Journal of Supercomputing.

Tsallis entropy: as a new single feature with the least computation time for classification of epileptic seizures

M. Pallikonda Rajasekaran, M. Thilagaraj, N. Arun Kumar, 2018, Cluster Computing.

An empirical mode decomposition (EMD)-based scheme for alcoholism identification

M. Thilagaraj, M. Pallikonda Rajasekaran, M. P. Rajasekaran, 2019, Pattern Recognit. Lett..

Smart Identification of Topographically Variant Anomalies in Brain Magnetic Resonance Imaging Using a Fish School-Based Fuzzy Clustering Approach

Yudong Zhang, Pallikonda Rajasekaran Murugan, Sakthivel Sankaran, 2020, IEEE Transactions on Fuzzy Systems.

An Adaptive MRI-PET Image Fusion Model Based on Deep Residual Learning and Self-Adaptive Total Variation

S. Selvendran, S. Jeevitha, M. Rajasekaran, 2022, Arabian Journal for Science and Engineering.

Indigenous Health Tracking Analyzer Using IoT

V. Muneeswaran, M. Rajasekaran, S. Reddy, 2021, 2021 6th International Conference on Communication and Electronics Systems (ICCES).

A hybrid deep learning based brain tumor classification and segmentation by stationary wavelet packet transform and adaptive kernel fuzzy c means clustering

M. Rajasekaran, R. Devi, B. Perumal, 2022, Adv. Eng. Softw..

Multimodality image fusion using centre-based genetic algorithm and fuzzy logic

Murugan Pallikonda Rajasekaran, Subbiah Parvathy Velmurugan, Pothiraj Sivakumar, 2018 .

Brain and Pancreatic Tumor Classification Based on GLCM—k-NN Approaches

M. Pallikonda Rajasekaran, G. Vishnuvarthanan, D. Jithendra Reddy, 2018, Advances in Intelligent Systems and Computing.

Identification of drivers drowsiness based on features extracted from EEG signal using SVM classifier

M. Thilagaraj, M. Rajasekaran, U. Ramani, 2021, 3C Tecnología_Glosas de innovación aplicadas a la pyme.

IoT based Multiple Vital Health Parameter Detection and Analyzer System

V. Muneeswaran, P. Nagaraj, M. Rajasekaran, 2022, 2022 7th International Conference on Communication and Electronics Systems (ICCES).

A robust multi-utility neural network technique integrated with discriminators for bone health decisioning to facilitate clinical-driven processes

Yudong Zhang, V. Govindaraj, Arunprasath Thiyagarajan, 2023, Research on Biomedical Engineering.

VLSI Implementation of Image Compression using TSA Optimized Discrete Wavelet Transform Techniques

K. Muthamil Sudar, P. Nagaraj, V. Muneeswaran, 2020, 2020 Third International Conference on Smart Systems and Inventive Technology (ICSSIT).

Classification of EEG Signals on Standing, Walking and Running Dataset using LSTM-RNN

Vaibhav Gandhi, R. Ramalakshmi, M. Rajasekaran, 2022, 2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N).

Development of a combinational framework to concurrently perform tissue segmentation and tumor identification in T1 - W, T2 - W, FLAIR and MPR type magnetic resonance brain images

Yudong Zhang, M. Pallikonda Rajasekaran, Vishnuvarthanan Govindaraj, 2018, Expert Syst. Appl..

Epileptic Seizure Mining via Novel Empirical Wavelet Feature with J48 and KNN Classifier

M. Pallikonda Rajasekaran, M. Thilagaraj, M. Thilagaraj, 2018 .

Automatic segmentation of gallbladder using bio-inspired algorithm based on a spider web construction model

V. Muneeswaran, M. Pallikonda Rajasekaran, V. Muneeswaran, 2019, The Journal of Supercomputing.

FILTERING OF MAGNETIC RESONANCE IMAGES USING AN ADAPTIVE HYBRIDIZED FUZZY FILTER

M. Rajasekaran, R. Devi, B. Perumal, 2020, Indian Journal of Computer Science and Engineering.

Sign Language Translator Using LabVIEW Enabled with Internet of Things

M. Pallikonda Rajasekaran, M. Pradeep Kumar, M. Thilagaraj, 2018, Smart Intelligent Computing and Applications.

Implementation of Automatic Soil Moisture Dearth Test and Data Exertion Using Internet of Things

P. Nagaraj, V. Muneeswaran, M. Pallikonda Rajasekaran, 2021, Advances in Intelligent Systems and Computing.

An automated hybrid approach using clustering and nature inspired optimization technique for improved tumor and tissue segmentation in magnetic resonance brain images

Yudong Zhang, M. Pallikonda Rajasekaran, Vishnuvarthanan Govindaraj, 2017, Appl. Soft Comput..

Multi-channeled MR brain image segmentation: A novel double optimization approach combined with clustering technique for tumor identification and tissue segmentation

Yudong Zhang, M. Pallikonda Rajasekaran, Vishnuvarthanan Govindaraj, 2019, Biocybernetics and Biomedical Engineering.

Automatic knee joint segmentation using Douglas-Rachford splitting method

C. Rini, M. Rajasekaran, B. Perumal, 2019, Multimedia tools and applications.

Automatic Segmentation of Gallbladder Using Intuitionistic Fuzzy Based Active Contour Model

V. Muneeswaran, M. Pallikonda Rajasekaran, V. Muneeswaran, 2018, Lecture Notes in Electrical Engineering.

Local Contrast Regularized Contrast Limited Adaptive Histogram Equalization Using Tree Seed Algorithm—An Aid for Mammogram Images Enhancement

V. Muneeswaran, M. Pallikonda Rajasekaran, V. Muneeswaran, 2018, Smart Intelligent Computing and Applications.

Beltrami-Regularized Denoising Filter Based on Tree Seed Optimization Algorithm: An Ultrasound Image Application

V. Muneeswaran, M. Pallikonda Rajasekaran, V. Muneeswaran, 2017 .

Automated unsupervised learning-based clustering approach for effective anomaly detection in brain magnetic resonance imaging (MRI)

Yudong Zhang, M. Pallikonda Rajasekaran, Vishnuvarthanan Govindaraj, 2020, IET Image Process..

Programmed Identification of Glaucoma Using Tree Seed Optimized Histogram Manipulation

P. Nagaraj, V. Muneeswaran, M. Pallikonda Rajasekaran, 2021, Advances in Intelligent Systems and Computing.

EEG signal classification using Principal Component Analysis with Neural Network in Brain Computer Interface applications

B. Kannapiran, M. P. Rajasekaran, R. Kottaimalai, 2013, 2013 IEEE International Conference ON Emerging Trends in Computing, Communication and Nanotechnology (ICECCN).

Elderly patient monitoring system using a wireless sensor network.

P. Subbaraj, S. Radhakrishnan, M. Pallikonda Rajasekaran, 2009, Telemedicine journal and e-health : the official journal of the American Telemedicine Association.