A novel two-stage optimized model for logo-based document image retrieval based on a soft computing framework

2020 ◽  
Author(s):  
K. Raveendra ◽  
T. Karthikeyan ◽  
Vinothkanna Rajendran ◽  
P. V. N. Reddy
Keyword(s):  
Image Retrieval ◽  
Soft Computing ◽  
Document Image ◽  
Two Stage ◽  
Optimized Model ◽  
Computing Framework

scholarly journals A comparative study of different texture features for document image retrieval

2019 ◽  
Vol 121 ◽  
pp. 97-114 ◽  
Author(s):  
Fahimeh Alaei ◽  
Alireza Alaei ◽  
Umapada Pal ◽  
Michael Blumenstein
Keyword(s):  
Comparative Study ◽  
Image Retrieval ◽  
Texture Features ◽  
Document Image

scholarly journals The Role and Utilization of CNN in Automatic Logo Based Document Image Retrieval Methods

2018 ◽  
Vol 7 (3.1) ◽  
pp. 13
Author(s):  
Raveendra K ◽  
R Vinoth Kanna
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Feature Extraction ◽  
Image Retrieval ◽  
Convolutional Neural Network ◽  
Convolutional Neural Networks ◽  
Document Image ◽  
Retrieval Process ◽  
Pictorial Representations

Automatic logo based document image retrieval process is an essential and mostly used method in the feature extraction applications. In this paper the architecture of Convolutional Neural Network (CNN) was elaborately explained with pictorial representations in order to understand the complex Convolutional Neural Networks process in a simplified way. The main objective of this paper is to effectively utilize the CNN in the process of automatic logo based document image retrieval methods.  

Prediction of rock strain using soft computing framework

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
T. Pradeep ◽  
Abidhan Bardhan ◽  
Pijush Samui
Keyword(s):  
Soft Computing ◽  
Computing Framework
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