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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM18689

OBJECT DETECTION AND ESTIMATING THE DISTANCE BETWEEN DETECTED OBJECTS USING DEEP LEARNING ALGORITHMS

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM18689

Volume:

7 |

4 |

Apr 2023

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

VEC

VUNNAM ESWAR CHANDU

CH

CHAGARLAMUDI HARSHITHA

VNS

VENNA NAVYA SREE

EG

ELURI GANESH

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Abstract

Object detection is a computer vision technique that allows us to identify and locate objects in an image. Computer vision is a field of artificial intelligence that trains computers to interpret and understand the visual world. Object detection involves a bounding box around each object in the image and distance should be estimated between objects. It is used to identify the objects in a given image like person, bicycle, dog etc. With this kind of identification and localization, object detection can be used to count objects in a scene and determine and track their precise locations, all while accurately labeling them. In our project we are using the COCO dataset and YOLOv3 using a deep learning method.

KEYWORDS

Deep learning-YOLO a monocular camera distance calculation and object identification

Cite This Article

VUNNAM ESWAR CHANDU, CHAGARLAMUDI HARSHITHA, VENNA NAVYA SREE, ELURI GANESH, "OBJECT DETECTION AND ESTIMATING THE DISTANCE BETWEEN DETECTED OBJECTS USING DEEP LEARNING ALGORITHMS," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 4, Apr 2023. https://doi.org/10.55041/IJSREM18689

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Publication Date

6/3/2023

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The authors declare no conflict of interest related to this research work.

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