Nov 1, 2021 · In this paper, we propose a method of generating adversarial examples in the license plate, which has no human feedback and is difficult to identify by humans.
Nov 1, 2021 · In this paper, we propose a method of generating adversarial examples in the license plate, which has no human feedback and is difficult to identify by humans.
Aug 7, 2024 · Deep learning technology has been used to develop improved license plate recognition (LPR) systems. In particular, deep neural networks have ...
In the proposed method, adversarial noise is added only to the license plate among the entire image to create an adversarial example that is erroneously ...
Jun 1, 2024 · Adversarial examples in LPR systems are crafted by introducing perturbations to original license plate images, which can effectively compromise ...
People also ask
How accurate is the license plate recognition?
What are the algorithms for license plate detection?
What is a license plate detector?
Nov 1, 2021 · Deep learning technology has been used to develop improved license plate recognition (LPR) systems. In particular, deep neural networks have ...
A dual adversarial attack method was proposed for license plate recognition (LPR) systems in a DNN-based scenario.
In this paper, we propose an evasion attack on CNN classifiers in the context of License Plate Recognition (LPR), which adds predetermined perturbations to ...
Abstract: The license plate recognition system (LPRS) has been widely adopted in daily life due to its efficiency and high accuracy.
Oct 27, 2019 · In this paper, we propose an evasion attack on CNN classifiers in the context of License Plate Recognition (LPR), which adds predetermined perturbations to ...
Missing: Adv- | Show results with:Adv-