Smart Application for Real Time Detection: An Improved Lightweight Detector for Real-Time Vehicle Detection

Document Type

Conference Proceeding

Source of Publication

2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)

Publication Date

7-7-2023

Abstract

With the goal of creating a model that satisfies the demands of detecting vehicles on the road in real time and delivers high FPS speed and high accuracy, we propose enhancements to the YOLOv4-tiny detector in this work. We suggest a modification to the FPN to increase the semantic and location information between the higher and lower levels. Also, to further solve the issue with NMS, we employed soft-NMS in our model. Moreover, to address the drawbacks of the IoU, we proposed a way to improve anchor clustering. The experimental results show that our proposed model outperforms the basic model with 3.29% higher mAP and 1.17 higher FPS.

ISBN

979-8-3503-3538-5

Publisher

IEEE

Volume

00

First Page

481

Last Page

486

Disciplines

Computer Sciences

Keywords

Location awareness, Roads, Semantics, Road vehicles, Detectors, Predictive models, Real-time systems

Indexed in Scopus

no

Open Access

no

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