A GAN-augmented CNN and ViT pipeline reports 88-95% accuracy for traffic accident detection on a CCTV frame dataset, but the GAN's contribution is never isolated.
Generative adversarial networks (GANs) for image augmentation in agriculture: A sys- tematic review,
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Integrating Generative Adversarial Networks and Convolutional Neural Networks for Enhanced Traffic Accidents Detection and Analysis
A GAN-augmented CNN and ViT pipeline reports 88-95% accuracy for traffic accident detection on a CCTV frame dataset, but the GAN's contribution is never isolated.