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Authors: Shubham Dubey 1 ; J. Satyanarayana 2 and C. Mohan 1

Affiliations: 1 Computer Science Department, Indian Institute of Technology Hyderabad, Hyderabad, India ; 2 RCI-DRDO, India

Keyword(s): Object Detection, YOLO, False Positive, Variational Autoencoders.

Abstract: Object detection is an important task in computer vision systems, encompassing a diverse spectrum of applications, including but not limited to autonomous vehicular navigation and surveillance. Despite considerable advancements in object detection models such as YOLO, the issue of false positive detections remain a prevalent concern, thereby causing misclassifications and diminishing the reliability of these systems. This research endeavors to present an innovative methodology designed to augment object detection accuracy by incorporating Variational Autoencoders (VAEs) as a filtration mechanism within the YOLO framework. This integration seeks to rectify the issue of false positive detections, ultimately fostering a marked enhancement in detection precision and strengthening the overall dependability of object detection systems.

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Paper citation in several formats:
Dubey, S.; Satyanarayana, J. and Mohan, C. (2024). Enhancing Object Detection Accuracy with Variational Autoencoders as a Filter in YOLO. In Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP; ISBN 978-989-758-679-8; ISSN 2184-4321, SciTePress, pages 270-277. DOI: 10.5220/0012347700003660

@conference{visapp24,
author={Shubham Dubey. and J. Satyanarayana. and C. Mohan.},
title={Enhancing Object Detection Accuracy with Variational Autoencoders as a Filter in YOLO},
booktitle={Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP},
year={2024},
pages={270-277},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012347700003660},
isbn={978-989-758-679-8},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP
TI - Enhancing Object Detection Accuracy with Variational Autoencoders as a Filter in YOLO
SN - 978-989-758-679-8
IS - 2184-4321
AU - Dubey, S.
AU - Satyanarayana, J.
AU - Mohan, C.
PY - 2024
SP - 270
EP - 277
DO - 10.5220/0012347700003660
PB - SciTePress

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