UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
Call for Paper
Volume 11 | Issue 3 | March 2024

JETIREXPLORE- Search Thousands of research papers



WhatsApp Contact
Click Here

Published in:

Volume 8 Issue 6
June-2021
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

7.95 impact factor calculated by Google scholar

Unique Identifier

Published Paper ID:
JETIR2106714


Registration ID:
311456

Page Number

f103-f108

Share This Article


Jetir RMS

Title

Classification of Images using Transfer Learning

Abstract

For better accuracy and faster convergence, image classification using Transfer Learning and deep feed-forward neural networks (DFNN) is important. We have used existing models in Transfer Learning that save training time, improve neural network performance, and do not require a lot of data. A number of image classification models have been developed so far that articulates the major issue concerned with recognition accuracy. Image recognition is the most critical problem encountered in the areas applying practical applications of Computer Vision. The attribute of Object Recognition governed by autonomous vehicles with robotic influences, obstacle or pedestrian detection system, etc are few of the practical examples dealing with recognition accuracy. Machine learning, especially neural networks like the (DFNN) that won image classification competitions, has received a lot of attention. Such a DFNN architecture model should be researched and investigated, according to this article. Using new image datasets to see if Transfer Learning will perform better in terms of precision and productivity. There are some similarities to state-of-the-art approaches. The DFNN can be tweaked by changing the total number of hidden layers, hidden neurons in each hidden layer, and the number of connections made in between layers.

Key Words

Transfer Learning (TL) · Hidden neurons (HN) · Hidden layer (HL) · Tabu search (TS) · Deep feed-forward neural network (DFNN)

Cite This Article

"Classification of Images using Transfer Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 6, page no.f103-f108, June-2021, Available :http://www.jetir.org/papers/JETIR2106714.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Classification of Images using Transfer Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 6, page no. ppf103-f108, June-2021, Available at : http://www.jetir.org/papers/JETIR2106714.pdf

Publication Details

Published Paper ID: JETIR2106714
Registration ID: 311456
Published In: Volume 8 | Issue 6 | Year June-2021
DOI (Digital Object Identifier):
Page No: f103-f108
Country: Lucknow, Uttar Pradesh, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


Preview This Article


Downlaod

Click here for Article Preview

Download PDF

Downloads

000558

Print This Page

Current Call For Paper

Jetir RMS