How to Cite
Abstract
With the increasing relevance of convolutional neural network (CNN) based perception for AVs, there has been a growing interest in understanding the vulnerability of CNNs to adversarial perturbations. Despite the majority of the work addressing image classification problems, novel defenses benefit general technologies. This research addresses an underrated possible percentage of the aerospace technology. To empirically estimate the effectiveness of adversarial training to alleviate the visual analytics vulnerabilities of AV perception modules, we conduct in the past exceedingly other specialized and transfer learning techniques.
References
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