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 5 Issue 9
September-2018
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:
JETIRA006301


Registration ID:
188770

Page Number

230-235

Share This Article


Jetir RMS

Title

OBJECT DETECTION AND CLASSIFICATION THROUGH DEEP LEARNING APPROACHES

Abstract

In this paper, we implemented the image classification and object detection. This paper presents a deep learning approach for traffic light detection in adapting a single shot detection(SSD) approach and image classification of two categories of bicycle by retraining inceptionv3 model both using an open source tool called TensorFlow Object Detection API. We reviewed the current literature on convolutional object detection and tested the implementability of one of the methods and discovered that convolutional object detection is still evolving as a technology despite that convolutional object detection has outranked other object detection methods. To implement object detection and image classification there is free availability of datasets and pre-trained networks it is possible to create a functional implementation of a deep neural network without access to specialist hardware.

Key Words

Object detection, Deep learning, Convolutional neural network, TensorFlow Object Detection API, SSD model, InceptionV3, InceptionV2.

Cite This Article

"OBJECT DETECTION AND CLASSIFICATION THROUGH DEEP LEARNING APPROACHES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 9, page no.230-235, September-2018, Available :http://www.jetir.org/papers/JETIRA006301.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

"OBJECT DETECTION AND CLASSIFICATION THROUGH DEEP LEARNING APPROACHES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 9, page no. pp230-235, September-2018, Available at : http://www.jetir.org/papers/JETIRA006301.pdf

Publication Details

Published Paper ID: JETIRA006301
Registration ID: 188770
Published In: Volume 5 | Issue 9 | Year September-2018
DOI (Digital Object Identifier):
Page No: 230-235
Country: --, -, - .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


Preview This Article


Downlaod

Click here for Article Preview

Download PDF

Downloads

0003002

Print This Page

Current Call For Paper

Jetir RMS