Real-Time Classification of Green Coffee Beans by Using a Convolutional Neural Network

Author(s):  
Nen-Fu Huang ◽  
Dong-Lin Chou ◽  
Chia-An Lee
2020 ◽  
Vol 2 (4) ◽  
pp. 167-172
Author(s):  
Nen-Fu Huang ◽  
Dong-Lin Chou ◽  
Chia-An Lee ◽  
Feng-Ping Wu ◽  
An-Chi Chuang ◽  
...  

Author(s):  
Amal Bouti ◽  
Mohamed Adnane Mahraz ◽  
Jamal Riffi ◽  
Hamid Tairi

In this chapter, the authors report a system for detection and classification of road signs. This system consists of two parts. The first part detects the road signs in real time. The second part classifies the German traffic signs (GTSRB) dataset and makes the prediction using the road signs detected in the first part to test the effectiveness. The authors used HOG and SVM in the detection part to detect the road signs captured by the camera. Then they used a convolutional neural network based on the LeNet model in which some modifications were added in the classification part. The system obtains an accuracy rate of 96.85% in the detection part and 96.23% in the classification part.


Author(s):  
Rayner H. Montes Condori ◽  
Juan H. Chuctaya Humari ◽  
Christian E. Portugal-Zambrano ◽  
Juan C Gutierrez-Caceres ◽  
Cesar A. Beltran-Castanon

Sign in / Sign up

Export Citation Format

Share Document