UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 10 Issue 6
June-2023
eISSN: 2349-5162

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

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Published Paper ID:
JETIRTHE2047


Registration ID:
513299

Page Number

d1-d30

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Title

PREDICT PLANT GROWTH AND YIELD IN GREENHOUSE ENVIRONMENTS USING DEEP LEARNING

Abstract

Currently, global companies are developing technologies for advanced self-driving cars, which is in the 4th stage. Self-driving cars are being developed based on various ICT technologies, and the principle of operation can be classified into three levels recognition, judgment, and control. The recognition step is to recognize and collect information about surrounding situations by utilizing various sensors in vehicles such as GPS, camera, and radar. The judgment step determines the driving strategy based on the recognized information. Then, this step identifies and analyzes the conditions in which the vehicle is placed, and determines the driving plans appropriate to the driving environment and the objectives. The control step determines the speed, direction, etc. of the driving and the vehicle starts driving on its own. An autonomous driving vehicle performs various actions to arrive at its destination, repeating the steps of recognition, judgment, and control on its own.

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"PREDICT PLANT GROWTH AND YIELD IN GREENHOUSE ENVIRONMENTS USING DEEP LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 6, page no.d1-d30, June-2023, Available :http://www.jetir.org/papers/JETIRTHE2047.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

"PREDICT PLANT GROWTH AND YIELD IN GREENHOUSE ENVIRONMENTS USING DEEP LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 6, page no. ppd1-d30, June-2023, Available at : http://www.jetir.org/papers/JETIRTHE2047.pdf

Publication Details

Published Paper ID: JETIRTHE2047
Registration ID: 513299
Published In: Volume 10 | Issue 6 | Year June-2023
DOI (Digital Object Identifier):
Page No: d1-d30
Country: ANAKAPALLI, ANDHRA PRADESH, India .
Area: Science
ISSN Number: 2349-5162
Publisher: IJ Publication


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