... using Canny,
Principal Component Analysis (PCA) and Artificial Neural
Network (ANN) apply for facial expression classification.
Canny and PCA apply for local facial feature extraction. A
facial ... with Rapid Facial Expression
Classification Using Artificial Neural Network [10], Facial
Expression Classification Using Multi Artificial Neural...
... (Canny_PCA_ANN) improved the
Classification Accuracy than
Rapid Facial Expression
Classification Using Artificial Neural Networks [10] and
Facial Expression Classification Using Multi Artificial ... proposal method.
Index Terms— Artificial Neural Network (ANN), Canny,
Facial Expression Classification, Principal Component Analysis
(PCA).
I. I
NT...
...
as feed-forward neural network and back propagation are its
fast training speed and local feature convergence [12]. Thus,
in this paper, RBF neural network is used as a classifier in a
facial ...
communications. For facial expression classification, data
from static images or video sequences are used. In fact, there
have been many approaches for facial expressio...
... classic statistical technique of factor
analysis (FA). It is called principal factor analysis [166]. Generally, the goal in factor
analysis is different from PCA. Factor analysis was originally ... 6
Principal Component
Analysis and Whitening
Principal component analysis (PCA) and the closely related Karhunen-Lo
`
eve trans-
form, or the Hotelling transform, are clas...
... on JAFFE database consisting 213 images posed by
10 Japanese female models.
Keywords: Facial Expression, Multi Artificial Neural Network
(MANN), 2D -Principal Component Analysis (2D-PCA).
1. ... This is a wrong
result classification.
One other approach is popular at present is to use Artificial
Neural Network for the pattern classification. Artificial
Neural...
... many Neural
Networks together, so we call it Multi Artificial Neural Network (MANN).
3 Multi Artificial Neural Network apply for image classification
3.1 The proposal MANN model
Multi Artificial ... Artificial Neural Network (MANN), applying for pattern or image
classification with parameters (m, L), has m Sub -Neural Network (SNN) and a global
frame (G...
... results are used. 43 learning data are used for
training the ANN model, and the others are used for the comparison
Data Collection
Data Normalization
Parametric Studies
Training and Testing ANN ... the field data. In
particular, these differences are increase at the high strain rate range.
The reason is that ANN model has not a lot of database on the high
strain rate. To elimina...
... Average reaction times and errors for the grapheme frequency and grapheme entropy (uncertainty)
manipulations (standard deviations are indicated into parentheses) in the immediate and delayed naming ... in a immediate naming and a
delayed naming task with the same stimuli. In the
immediate naming condition, participants were
instructed to read aloud pseudowords as quickly
and...
... Probabilistic Latent Semantic Analysis
with Principal Component Analysis
Ayman Farahat
Palo Alto Research Center
3333 Coyote Hill Road
Palo Alto, CA 94304
ayman.farahat@gmail.com
Francine Chen
Palo ... 1 PLSA, and 1 LSA-
PLSA model and 2) 1 LSA-PLSA with 3 PLSA
models. We also compared these models against
the performance of an averaged model without an
LSA-PLSA model: 1 LSA and...