English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Facial Expression Classification is an interesting research problem in recentyears. There are a lot of methods to solve this problem. In this research, wepropose a novel approach using Canny, Principal Component Analysis (PCA) andArtificial Neural Network. Firstly, in preprocessing phase, we use Canny forlocal region detection of facial images. Then each of local region's featureswill be presented based on Principal Component Analysis (PCA). Finally, usingArtificial Neural Network (ANN)applies for Facial Expression Classification. Weapply our proposal method (Canny_PCA_ANN) for recognition of six basic facialexpressions on JAFFE database consisting 213 images posed by 10 Japanese femalemodels. The experimental result shows the feasibility of our proposal method.

A Facial Expression Classification System Integrating Canny, Principal Component Analysis and Artificial Neural Network