This research presents a novel approach for feature extraction in image understanding, utilizing an AT-ConvLSTM-based Cultural Algorithm. The Proposed CA-AT-ConvLSTM leverages the power of deep learning through AT-ConvLSTM architecture while optimizing the feature extraction process using Cultural Algorithms. This synergistic approach enhances the efficiency and accuracy of image understanding tasks, making it suitable for a wide range of applications, from computer vision to pattern recognition. The experimental results demonstrate the superiority of the proposed technique over traditional methods, highlighting its potential in advancing the field of image analysis.
Shweta Nishit Jain, Priya Pise and Akhilesh Mishra
Shri Jagdishprasad Jhabarmal Tibrewala University, India
Feature Extraction, AT-ConvLSTM, Cultural Algorithm, Image Understanding, Deep learning
| January | February | March | April | May | June | July | August | September | October | November | December |
| 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 0 | 0 |
| Published By :
ICTACT
Published In :
ICTACT Journal on Image and Video Processing
( Volume: 14 , Issue: 1 , Pages: 3066 - 3072 )
Date of Publication :
August 2023
Page Views :
627
Full Text Views :
16
|