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 …
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
Nowadays, many deep models have been presented to recognize emotions using
electroencephalogram (EEG) signals. These deep models are computationally intensive, it …
electroencephalogram (EEG) signals. These deep models are computationally intensive, it …
Developed Newton-Raphson based deep features selection framework for skin lesion recognition
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 …
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 …
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 …
spectrum disorder (ASD), little research has focused on the sex differences in sensory …
Multilinear discriminant analysis for face recognition
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 …
the excessive dimension of the data space often brings the algorithms into the curse of …
Deep transfer learning in diagnosing leukemia in blood cells
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 …
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 …
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
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 …
transformations called" Locally Linear Discriminant Analysis"(LLDA). The underlying idea is …
A unified framework for subspace face recognition
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 …
recognition approaches. In this paper, we show that they can be unified under the same …