To: Author

Article Fingerprint
ReserarchID
CSTELDK0
Choose where you want to hide AI Takeaway. Your site-wide choice will be remembered in this browser.
Computer vision is concerned with the automatic extraction, analysis, and understanding of useful information from a single image or a sequence of images. We have used Convolutional Neural Networks (CNN) in automatic image classification systems. In most cases, we utilize the features from the top layer of the CNN for classification; however, those features may not contain enough useful information to predict an image correctly. In some cases, features from the lower layer carry more discriminative power than those from the top. Therefore, applying features from a specific layer only to classification seems to be a process that does not utilize learned CNN’s potential discriminant power to its full extent. Because of this property we are in need of fusion of features from multiple layers. We want to create a model with multiple layers that will be able to recognize and classify the images. We want to complete our model by using the concepts of Convolutional Neural Network and CIFAR-10 dataset. Moreover, we will show how MatConvNet can be used to implement our model with CPU training as well as less training time. The objective of our work is to learn and practically apply the concepts of Convolutional Neural Network.
Md. Anwar Hossain, Md. Shahriar Alam Sajib. 2019. "Classification of Image using Convolutional Neural Network (CNN)". Global Journal of Computer Science and Technology - D: Neural & AI GJCST-D Volume 19 (GJCST Volume 19 Issue D2).
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
v1.2
Explore published articles in an immersive Augmented Reality environment. Our platform converts research papers into interactive 3D books, allowing readers to view and interact with content using AR and VR compatible devices.
Your published article is automatically converted into a realistic 3D book. Flip through pages and read research papers in a more engaging and interactive format.
Total Score: 142
Country: Bangladesh
Subject: Global Journal of Computer Science and Technology
Authors: Md. Anwar Hossain, Md. Shahriar Alam Sajib (PhD/Dr. count: 0)
View Count (all-time): 408
Total Views (Real + Logic): 2238
Total Downloads (simulated): 113
Publish Date: 2019 01, Tue
Monthly Totals (Real + Logic):
We use cookies and similar technologies to improve site performance, understand traffic, and enhance your publishing experience. Cookie Policy
Choose which optional cookies Global Journals can use. Your preference applies across this platform and can be updated any time.
These cookies are required for core website functionality and security.
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.