Proceedings of the International Conference on Sustainable Innovation with Artificial Intelligence and Machine Learning 2025 (ICSIAIML 2025)

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Multimedia Object Detection

Authors
P. Rahul Das1, *, B. Venkateswarlu2, G. Vijay Kumar3
1Geethanjali College of Engineering and Technology, Hyderabad, Telangana, India
2Geethanjali College of Engineering and Technology, Hyderabad, Telangana, India
3Geethanjali College of Engineering and Technology, Hyderabad, Telangana, India
*Corresponding author. Email: rahuldaspathlavath@gmail.com
Corresponding Author
P. Rahul Das
Available Online 6 January 2026.
DOI
10.2991/978-94-6463-948-3_24How to use a DOI?
Keywords
Convolutional Neural Networks; Only Look Once; Single Shot MultiBox Detector
Abstract

Multimedia object detection technology has been a major factor in changing the world industries. It has enabled machines to see and understand visual content which in turn has changed application domains like smart surveillance, healthcare, and e-commerce to name a few, very differently. For example, in the case of security, this ability allows cameras to detect abnormal behavior and movement activities, and also identify suspects instantly. While in healthcare, it supports the process of early medical diagnosis through detecting tumors or broken bones in medical images like X-Rays, MRIs, and CT scans to facilitate effective treatments. Besides that, object detection can also be used by e-commerce platforms to automatically categorize products in a neat and efficient way while removing the wrong type of content. As compared with their predecessors, YOLO, Faster R-CNN and SSD, are new-age models that can operate fast while keeping high detection precision and can locate several objects in complicated surroundings. When combined with the technological advances in GPUs, TPUs, and edge AI, it is conceivable to achieve real-time object detection on mobile phones, drones, and IoT gadgets. Hence, as a result, this technology can be used in various industries such as commercial vehicles and smart city infrastructure to name a few.

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 Sustainable Innovation with Artificial Intelligence and Machine Learning 2025 (ICSIAIML 2025)
Series
Advances in Intelligent Systems Research
Publication Date
6 January 2026
ISBN
978-94-6463-948-3
ISSN
1951-6851
DOI
10.2991/978-94-6463-948-3_24How 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  - P. Rahul Das
AU  - B. Venkateswarlu
AU  - G. Vijay Kumar
PY  - 2026
DA  - 2026/01/06
TI  - Multimedia Object Detection
BT  - Proceedings of the International Conference on Sustainable Innovation with Artificial Intelligence and Machine Learning 2025 (ICSIAIML 2025)
PB  - Atlantis Press
SP  - 335
EP  - 341
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-948-3_24
DO  - 10.2991/978-94-6463-948-3_24
ID  - Das2026
ER  -