Face recognition: A literature survey

W Zhao, R Chellappa, PJ Phillips… - ACM computing surveys …, 2003 - dl.acm.org
As one of the most successful applications of image analysis and understanding, face
recognition has recently received significant attention, especially during the past several …

PrimePatNet87: prime pattern and tunable q-factor wavelet transform techniques for automated accurate EEG emotion recognition

A Dogan, M Akay, PD Barua, M Baygin, S Dogan… - Computers in Biology …, 2021 - Elsevier
Nowadays, many deep models have been presented to recognize emotions using
electroencephalogram (EEG) signals. These deep models are computationally intensive, it …

Developed Newton-Raphson based deep features selection framework for skin lesion recognition

MA Khan, M Sharif, T Akram, SAC Bukhari… - Pattern Recognition …, 2020 - Elsevier
Melanoma is the fatal form of skin cancer; however, its diagnosis at the primary stages
significantly reduces the mortality rate. These days, the increasing numbers of skin cancer …

Convolutional neural network super resolution for face recognition in surveillance monitoring

P Rasti, T Uiboupin, S Escalera… - Articulated Motion and …, 2016 - Springer
Due to the importance of security in society, monitoring activities and recognizing specific
people through surveillance video cameras play an important role. One of the main issues in …

Sex differences in sensory processing in children with autism spectrum disorder

JMA Osório, B Rodríguez‐Herreros, S Richetin… - Autism …, 2021 - Wiley Online Library
Despite the high prevalence of sensory processing difficulties in children with autism
spectrum disorder (ASD), little research has focused on the sex differences in sensory …

Multilinear discriminant analysis for face recognition

S Yan, D Xu, Q Yang, L Zhang, X Tang… - IEEE Transactions on …, 2006 - ieeexplore.ieee.org
There is a growing interest in subspace learning techniques for face recognition; however,
the excessive dimension of the data space often brings the algorithms into the curse of …

Deep transfer learning in diagnosing leukemia in blood cells

M Loey, M Naman, H Zayed - Computers, 2020 - mdpi.com
Leukemia is a fatal disease that threatens the lives of many patients. Early detection can
effectively improve its rate of remission. This paper proposes two automated classification …

[图书][B] Subspace linear discriminant analysis for face recognition

W Zhao, R Chellappa, PJ Phillips - 1999 - Citeseer
In this paper we describe a holistic face recognition method based on subspace Linear
Discriminant Analysis (LDA). The method consists of two steps: rst we project the face image …

Locally linear discriminant analysis for multimodally distributed classes for face recognition with a single model image

TK Kim, J Kittler - IEEE transactions on pattern analysis and …, 2005 - ieeexplore.ieee.org
We present a novel method of nonlinear discriminant analysis involving a set of locally linear
transformations called" Locally Linear Discriminant Analysis"(LLDA). The underlying idea is …

A unified framework for subspace face recognition

X Wang, X Tang - IEEE Transactions on pattern analysis and …, 2004 - ieeexplore.ieee.org
PCA, LDA, and Bayesian analysis are the three most representative subspace face
recognition approaches. In this paper, we show that they can be unified under the same …