• Publications
  • Influence
GCV-Based Regularized Extreme Learning Machine for Facial Expression Recognition
TLDR
In this work, a new method of facial expression recognition is introduced where histogram of oriented gradients (HOG) feature extraction and GCV-based regularized ELM are applied. Expand
Accurate validation of GCV-based regularization parameter for extreme learning machine
TLDR
In this work, the Receiver Operating Characteristics (ROC) analysis is used to validate the regularization parameter obtained through GCV based method for ELM. Expand
Bat algorithm-based weighted Laplacian probabilistic neural network
TLDR
In this work, we propose the modifications to the existing PNN approach. Expand
Text Detection and Character Extraction in Natural Scene Images
TLDR
Text Information Extraction (TIE) System involves detecting text regions in a given image, localizing it, extracting the text part and recognizing text using OCR. Expand
Iterative minimal residual method provides optimal regularization parameter for extreme learning machines
TLDR
Regularization of ELM using Minimum Residual Method (MRM) and Golden-section line search . Expand
Optimized Laplacian Generalized Classifier Neural Network
TLDR
A new variant of Generalized Classifier Neural Network (GCNN) using population-based optimization Sine Cosine Algorithm with a novel fitness function. Expand
Smart Grid Communication Protocol Test Automation along with Protection Test Automation
TLDR
Automate the Protection Testing operation by integrating it with the Communication operation. Expand
Rising brics: a Path to multipolar world reality?
The discourse over change in the world order from a unipolar to multipolar has gained major attention in the recent times. While  the United States upholds the pivotal power position in the Expand
An automatic estimation of the ridge parameter for extreme learning machine.
TLDR
In this work, methods are proposed that use the L-curve and U-Curve techniques to automatically estimate the ridge parameter, and these methods are effective in the estimation of ridge parameter even for systems with larger data. Expand
Estimation of the Smoothing Parameter in Probabilistic Neural Network Using Evolutionary Algorithms
TLDR
The probabilistic neural network (PNN) is an efficient approach that can compute nonlinear decision boundaries, widely used for classification. Expand
...
1
2
...