Raghavendra U
Raghavendra U
Associate Professor, Manipal Institute of Technology
Verified email at manipal.edu - Homepage
Cited by
Cited by
Deep convolution neural network for accurate diagnosis of glaucoma using digital fundus images
U Raghavendra, H Fujita, SV Bhandary, A Gudigar, JH Tan, UR Acharya
Information Sciences 441, 41-49, 2018
A deep learning approach for Parkinson’s disease diagnosis from EEG signals
SL Oh, Y Hagiwara, U Raghavendra, R Yuvaraj, N Arunkumar, ...
Neural Computing and Applications, 1-7, 2018
Automated identification of shockable and non-shockable life-threatening ventricular arrhythmias using convolutional neural network
UR Acharya, H Fujita, SL Oh, U Raghavendra, JH Tan, M Adam, ...
Future Generation Computer Systems 79, 952-959, 2018
Automated characterization of fatty liver disease and cirrhosis using curvelet transform and entropy features extracted from ultrasound images
UR Acharya, U Raghavendra, H Fujita, Y Hagiwara, JEW Koh, TJ Hong, ...
Computers in biology and medicine 79, 250-258, 2016
A review on automatic detection and recognition of traffic sign
A Gudigar, S Chokkadi, U Raghavendra
Multimedia Tools and Applications 75 (1), 333-364, 2016
Application of Gabor wavelet and Locality Sensitive Discriminant Analysis for automated identification of breast cancer using digitized mammogram images
U Raghavendra, UR Acharya, H Fujita, A Gudigar, JH Tan, S Chokkadi
Applied Soft Computing 46, 151-161, 2016
Decision support system for fatty liver disease using GIST descriptors extracted from ultrasound images
UR Acharya, H Fujita, S Bhat, U Raghavendra, A Gudigar, F Molinari, ...
Information Fusion 29, 32-39, 2016
Age-related macular degeneration detection using deep convolutional neural network
JH Tan, SV Bhandary, S Sivaprasad, Y Hagiwara, A Bagchi, ...
Future Generation Computer Systems 87, 127-135, 2018
Application of multiresolution analysis for automated detection of brain abnormality using MR images: A comparative study
A Gudigar, U Raghavendra, TR San, EJ Ciaccio, UR Acharya
Future Generation Computer Systems 90, 359-367, 2019
Diagnosis of retinal health in digital fundus images using continuous wavelet transform (CWT) and entropies
JEW Koh, UR Acharya, Y Hagiwara, U Raghavendra, JH Tan, SV Sree, ...
Computers in biology and medicine 84, 89-97, 2017
Fusion of spatial gray level dependency and fractal texture features for the characterization of thyroid lesions
U Raghavendra, UR Acharya, A Gudigar, JH Tan, H Fujita, Y Hagiwara, ...
Ultrasonics 77, 110-120, 2017
Local texture patterns for traffic sign recognition using higher order spectra
A Gudigar, S Chokkadi, U Raghavendra, UR Acharya
Pattern Recognition Letters 94, 202-210, 2017
Digital camera identification using PRNU: A feature based approach
KR Akshatha, AK Karunakar, H Anitha, U Raghavendra, D Shetty
Digital Investigation 19, 69-77, 2016
Automated system for the detection of thoracolumbar fractures using a CNN architecture
U Raghavendra, NS Bhat, A Gudigar, UR Acharya
Future Generation Computer Systems 85, 184-189, 2018
Automated technique for coronary artery disease characterization and classification using DD-DTDWT in ultrasound images
U Raghavendra, H Fujita, A Gudigar, R Shetty, K Nayak, U Pai, J Samanth, ...
Biomedical Signal Processing and Control 40, 324-334, 2018
Novel expert system for glaucoma identification using non-parametric spatial envelope energy spectrum with fundus images
U Raghavendra, SV Bhandary, A Gudigar, UR Acharya
Biocybernetics and Biomedical Engineering 38 (1), 170-180, 2018
Automated categorization of multi-class brain abnormalities using decomposition techniques with MRI images: a comparative study
A Gudigar, U Raghavendra, EJ Ciaccio, N Arunkumar, E Abdulhay, ...
IEEE Access 7, 28498-28509, 2019
Multiple thresholding and subspace based approach for detection and recognition of traffic sign
A Gudigar, S Chokkadi, U Raghavendra, UR Acharya
Multimedia tools and applications 76 (5), 6973-6991, 2017
Optimized multi-level elongated quinary patterns for the assessment of thyroid nodules in ultrasound images
U Raghavendra, A Gudigar, M Maithri, A Gertych, KM Meiburger, ...
Computers in biology and medicine 95, 55-62, 2018
Automated screening tool for dry and wet age-related macular degeneration (ARMD) using pyramid of histogram of oriented gradients (PHOG) and nonlinear features
UR Acharya, Y Hagiwara, JEW Koh, JH Tan, SV Bhandary, AK Rao, ...
Journal of Computational Science 20, 41-51, 2017
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