Ratnakar Dash
Ratnakar Dash
Assistant professor,CSE Department , NIT Rourkela
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Brain MR image classification using two-dimensional discrete wavelet transform and AdaBoost with random forests
DR Nayak, R Dash, B Majhi
Neurocomputing 177, 188-197, 2016
Mammogram classification using two dimensional discrete wavelet transform and gray-level co-occurrence matrix for detection of breast cancer
S Beura, B Majhi, R Dash
Neurocomputing 154, 1-14, 2015
An early detection of low rate DDoS attack to SDN based data center networks using information distance metrics
KS Sahoo, D Puthal, M Tiwary, JJPC Rodrigues, B Sahoo, R Dash
Future Generation Computer Systems 89, 685-697, 2018
Motion blur parameters estimation for image restoration
R Dash, B Majhi
Optik 125 (5), 1634-1640, 2014
Automated breast cancer detection in digital mammograms: A moth flame optimization based ELM approach
D Muduli, R Dash, B Majhi
Biomedical Signal Processing and Control 59, 101912, 2020
Discrete ripplet-II transform and modified PSO based improved evolutionary extreme learning machine for pathological brain detection
DR Nayak, R Dash, B Majhi
Neurocomputing 282, 232-247, 2018
Toward secure software-defined networks against distributed denial of service attack
KS Sahoo, SK Panda, S Sahoo, B Sahoo, R Dash
The Journal of Supercomputing 75, 4829-4874, 2019
Automated pathological brain detection system: A fast discrete curvelet transform and probabilistic neural network based approach
DR Nayak, R Dash, B Majhi, V Prasad
Expert Systems with Applications 88, 152-164, 2017
Underwater fish species recognition using deep learning techniques
BV Deep, R Dash
2019 6th International Conference on Signal Processing and Integrated …, 2019
Combining extreme learning machine with modified sine cosine algorithm for detection of pathological brain
DR Nayak, R Dash, B Majhi, S Wang
Computers & Electrical Engineering 68, 366-380, 2018
Automated diagnosis of multi-class brain abnormalities using MRI images: a deep convolutional neural network based method
DR Nayak, R Dash, B Majhi
Pattern Recognition Letters 138, 385-391, 2020
Pathological brain detection using curvelet features and least squares SVM
DR Nayak, R Dash, B Majhi
Multimedia Tools and Applications 77, 3833-3856, 2018
Stationary wavelet transform and AdaBoost with SVM based pathological brain detection in MRI scanning
D Ranjan Nayak, R Dash, B Majhi
CNS & Neurological Disorders-Drug Targets (Formerly Current Drug Targets-CNS …, 2017
A deep stacked random vector functional link network autoencoder for diagnosis of brain abnormalities and breast cancer
DR Nayak, R Dash, B Majhi, RB Pachori, Y Zhang
Biomedical Signal Processing and Control 58, 101860, 2020
On the placement of controllers for designing a wide area software defined networks
KS Sahoo, S Sahoo, A Sarkar, B Sahoo, R Dash
TENCON 2017-2017 IEEE Region 10 Conference, 3123-3128, 2017
Second order difference based detection and directional weighted median filter for removal of random valued impulsive noise
PK Sa, R Dash, B Majhi
2009 International Conference on Industrial and Information Systems (ICIIS …, 2009
Hyperspectral image classification: A k-means clustering based approach
S Ranjan, DR Nayak, KS Kumar, R Dash, B Majhi
2017 4th International Conference on Advanced Computing and Communication …, 2017
Deep extreme learning machine with leaky rectified linear unit for multiclass classification of pathological brain images
DR Nayak, D Das, R Dash, S Majhi, B Majhi
Multimedia Tools and Applications 79, 15381-15396, 2020
An empirical evaluation of extreme learning machine: application to handwritten character recognition
D Das, DR Nayak, R Dash, B Majhi
Multimedia Tools and Applications 78, 19495-19523, 2019
Optimal controller selection in software defined network using a greedy-SA algorithm
KS Sahoo, B Sahoo, R Dash, N Jena
2016 3rd International Conference on Computing for Sustainable Global …, 2016
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