Proceedings of the International Conference on Advanced Materials, Manufacturing and Sustainable Development (ICAMMSD 2024)

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Real Time Object Identification: A Study on COCO Dataset

Authors
K. Govardhan Reddy1, S.Shanawaz Basha2, *
1Professor, Computer Science and Engineering, G. Pulla Reddy Engineering College, Kurnool, Andhra Pradesh, India
2Assistant Professor, Sridevi Women’s Engineering College, Hyderabad, Telangana, India
*Corresponding author. Email: shanawazbashaswec@gmail.com
Corresponding Author
S.Shanawaz Basha
Available Online 17 March 2025.
DOI
10.2991/978-94-6463-662-8_70How to use a DOI?
Keywords
Object identification; several pictures; Microsoft COCO dataset; Handling speeds; robust identification; YOLO model
Abstract

In computer vision, real-time object detection is a crucial problem with applications in a variety of fields, including robots, security monitoring systems, and driverless cars. The MS COCO (Common Objects in Context), is one of the most important datasets for object detection techniques. The purpose of this research is to investigate if the COCO dataset can be used for real-time object recognition. We list a few benefits of using this resource for the previously specified activities, including the ability to gather photographs in COCO, annotate the items of interest in detail, and provide reference performance metrics for this database. Next, we go over real-time object detection methods with the COCO dataset. This could entail developing structures that meet the needs of certain real-time settings or taking into account pre-made strategies like YOLO or SSD. The possible losses in the real-time model’s processing rate and model identification accuracy when using these models will also be taken into account in this research. Third, we take into account real-time object detection challenges, such as lighting, background clutter, and object occlusion. We examine the possibilities and methods to improve real-time object detection under different settings using the COCO dataset.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Advanced Materials, Manufacturing and Sustainable Development (ICAMMSD 2024)
Series
Advances in Engineering Research
Publication Date
17 March 2025
ISBN
978-94-6463-662-8
ISSN
2352-5401
DOI
10.2991/978-94-6463-662-8_70How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - K. Govardhan Reddy
AU  - S.Shanawaz Basha
PY  - 2025
DA  - 2025/03/17
TI  - Real Time Object Identification: A Study on COCO Dataset
BT  - Proceedings of the International Conference on Advanced Materials, Manufacturing and Sustainable Development (ICAMMSD 2024)
PB  - Atlantis Press
SP  - 860
EP  - 870
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-662-8_70
DO  - 10.2991/978-94-6463-662-8_70
ID  - Reddy2025
ER  -