Facial Expression Classification Using Vanilla Convolution Neural Network

2020 ◽  
Author(s):  
Lakshmi Sarvani Videla ◽  
P.M. Ashok Kumar
Keyword(s):  
Neural Network ◽  
Facial Expression ◽  
Convolution Neural Network ◽  
Facial Expression Classification ◽  
Expression Classification

scholarly journals Bare Skin Image Classification using Convolution Neural Network

2022 ◽  
Vol 12 (1) ◽  
pp. 138-145
Author(s):  
Jaya Gupta ◽  
◽  
Sunil Pathak ◽  
Gireesh Kumar
Keyword(s):  
Neural Network ◽  
Image Classification ◽  
Satellite Image ◽  
Activation Function ◽  
Convolution Neural Network ◽  
Classification Model ◽  
Significant Research ◽  
Research Problems ◽  
Facial Expression Classification ◽  
Expression Classification

Image classification is critical and significant research problems in computer vision applications such as facial expression classification, satellite image classification, and plant classification based on images. Here in the paper, the image classification model is applied for identifying the display of daunting pictures on the internet. The proposed model uses Convolution neural network to identify these images and filter them through different blocks of the network, so that it can be classified accurately. The model will work as an extension to the web browser and will work on all websites when activated. The extension will be blurring the images and deactivating the links on web pages. This means that it will scan the entire web page and find all the daunting images present on that page. Then we will blur those images before they are loaded and the children could see them. Keywords— Activation Function, CNN, Images Classification , Optimizers, VGG-19

scholarly journals A Novel Based 3d Facial Expression Detection Using Recurrent Neural Network

2020 ◽  
pp. 48-53
Author(s):  
Jaswanth K S ◽  
D. Stalin David
Keyword(s):  
Neural Network ◽  
Facial Expression ◽  
Facial Expressions ◽  
Social Relations ◽  
Recurrent Neural Network ◽  
Breakdown Point ◽  
Early Age ◽  
Facial Expression Classification ◽  
Expression Classification ◽  
Highlight Extraction

People periodically have diverse facial expressions and disposition changes in this way. Human facial expression acknowledgment plays a really energetic part in social relations. The acknowledgment of feelings has been an dynamic breakdown point from early age. The real-time location of facial expressions like appall, upbeat, pitiful, irate, anxious, astonish. The proposed framework can recognize 6 diverse facial expression. A facial expression acknowledgment framework needs to perform location and change to 3D image, then the facial highlight extraction, and facial expression classification is worn. Out proposed strategy we should be utilizing Recurrent Neural Network (RNN). This RNN show is prepared on JAFEE and Yale database dataset. This framework has capacity to screen individuals’ feelings, to segregate between feelings and name them fittingly.

Facial Expression Classification Based on Ensemble Convolutional Neural Network

2020 ◽  
Vol 57 (14) ◽  
pp. 141501
Author(s):  
周涛 Zhou Tao ◽  
吕晓琪 Lü Xiaoqi ◽  
任国印 Ren Guoyin ◽  
谷宇 Gu Yu ◽  
张明 Zhang Ming ◽  
...  
Keyword(s):  
Neural Network ◽  
Facial Expression ◽  
Convolutional Neural Network ◽  
Facial Expression Classification ◽  
Expression Classification
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