Preetha Phillips
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The state of modelling face processing in humans with deep learning Open
Deep learning models trained for facial recognition now surpass the highest performing human participants. Recent evidence suggests that they also model some qualitative aspects of face processing in humans. This review compares the curren…
Multiple Sclerosis Identification by 14-Layer Convolutional Neural Network With Batch Normalization, Dropout, and Stochastic Pooling Open
Aim: Multiple sclerosis is a severe brain and/or spinal cord disease. It may lead to a wide range of symptoms. Hence, the early diagnosis and treatment is quite important. Method: This study proposed a 14-layer convolutional neural network…
Multiple Sclerosis Identification Based on Fractional Fourier Entropy and a Modified Jaya Algorithm Open
Aim: Currently, identifying multiple sclerosis (MS) by human experts may come across the problem of “normal-appearing white matter”, which causes a low sensitivity. Methods: In this study, we presented a computer vision based approached to…
SYNTHETIC MINORITY OVERSAMPLING TECHNIQUE AND FRACTAL DIMENSION FOR IDENTIFYING MULTIPLE SCLEROSIS Open
Multiple sclerosis (MS) is a severe brain disease. Early detection can provide timely treatment. Fractal dimension can provide statistical index of pattern changes with scale at a given brain image. In this study, our team used susceptibil…
Preliminary research on abnormal brain detection by wavelet-energy and quantum- behaved PSO Open
It is important to detect abnormal brains accurately and early. The wavelet-energy (WE) was a successful feature descriptor that achieved excellent performance in various applications; hence, we proposed a WE based new approach for automat…
Tea Category Identification Using a Novel Fractional Fourier Entropy and Jaya Algorithm Open
This work proposes a tea-category identification (TCI) system, which can automatically determine tea category from images captured by a 3 charge-coupled device (CCD) digital camera. Three-hundred tea images were acquired as the dataset. Ap…
Facial Emotion Recognition Based on Biorthogonal Wavelet Entropy, Fuzzy Support Vector Machine, and Stratified Cross Validation Open
Emotion recognition represents the position and motion of facial muscles. It contributes significantly in many fields. Current approaches have not obtained good results. This paper aimed to propose a new emotion recognition system based on…
Multiple Sclerosis Detection Based on Biorthogonal Wavelet Transform, RBF Kernel Principal Component Analysis, and Logistic Regression Open
To detect multiple sclerosis (MS) diseases early, we proposed a novel method on the hardware of magnetic resonance imaging, and on the software of three successful methods: biorthogonal wavelet transform, kernel principal component analysi…
PATHOLOGICAL BRAIN DETECTION BY ARTIFICIAL INTELLIGENCE IN MAGNETIC RESONANCE IMAGING SCANNING (INVITED REVIEW) Open
Aim) Pathological brain detection (PBD) systems aim to assist and even replace neuroradiologists to make decisions for patients.This review offers a comprehensive and quantitative comparison for PBD systems by artificial intelligence in ma…