Static and Live Video Feed Image Processing using Deep Learning- A Review
Dr.S.Deepa
, Arulpreethi U P , Kaviya A B , Malathi V P
Recognization, Training Set, Customize, Accuracy.
One of the most intriguing uses of deep
learning isimage processing. By doing this, we may
teach a computer to perceive and comprehend visuals
in a manner comparable to that of a human. It
manages the picture class assignment task. One ofthe
oldest problems in picture classification is image
categorization. The purpose of this researchstudy is to
use deep neural networks (DNN), also known as deep
learning, to categorise an image using the framework
tensor. Google created the open source package called
Tensorflow specifically for use in deep learning
applications. Traditional machine learning is also
supported. Tensor recommends Python as a
programming language because it offers a simple
means of coupling high level abstractions. Therefore,
Python will be used to build the system.
"Static and Live Video Feed Image Processing using Deep Learning- A Review", TIJER - TIJER - INTERNATIONAL RESEARCH JOURNAL (www.TIJER.org), ISSN:2349-9249, Vol.11, Issue 2, page no.864-867, February-2024, Available :https://tijer.org/TIJER/papers/TIJERB001135.pdf
Volume 11
Issue 2,
February-2024
Pages : 864-867
Paper Reg. ID: TIJER_151071
Published Paper Id: TIJERB001135
Downloads: 000282
Research Area: Science and Technology
Country: THIRUVALLUR, TAMILNADU, India
ISSN: 2349-9249 | IMPACT FACTOR: 8.57 Calculated By Google Scholar | ESTD YEAR: 2014
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.57 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: TIJER (IJ Publication) Janvi Wave
