Empirical Evaluation of Convolutional Neural Networks Prediction Time in Classifying German Traffic Signs

2017 ◽  
Author(s):  
Joshua Fulco ◽  
Akanksha Devkar ◽  
Aravind Krishnan ◽  
Gregory Slavin ◽  
Carlos Morato
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Empirical Evaluation ◽  
Traffic Signs ◽  
Prediction Time

scholarly journals Newspaper Article Classification using Machine Learning Techniques

2020 ◽  
Vol 9 (5) ◽  
pp. 872-877
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
Convolutional Neural Networks ◽  
Machine Learning Techniques ◽  
Learning Approach ◽  
Training Time ◽  
Time Prediction ◽  
Learning Techniques ◽  
Prediction Time ◽  
Newspaper Articles

Newspaper articles offer us insights on several news. They can be one of many categories like sports, politics, Science and Technology etc. Text classification is a need of the day as large uncategorized data is the problem everywhere. Through this study, We intend to compare several algorithms along with data preprocessing approaches to classify the newspaper articles into their respective categories. Convolutional Neural Networks(CNN) is a deep learning approach which is currently a strong competitor to other classification algorithms like SVM, Naive Bayes and KNN. We hence intend to implement Convolutional Neural Networks - a deep learning approach to classify our newspaper articles, develop an understanding of all the algorithms implemented and compare their results. We also attempt to compare the training time, prediction time and accuracies of all the algorithms.

scholarly journals Convolutional Neural Networks for Croatian Traffic Signs Recognition

2014 ◽  
Author(s):  
Vedran Vukotić ◽  
Josip Krapac ◽  
Siniša Šegvić
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Traffic Signs
Sign in / Sign up

Export Citation Format

Share Document