Quantization Effects on Neural Networks Perception: How would quantization change the perceptual field of vision models?

arXiv:2403.09939v1 Announce Type: new
Abstract: Neural network quantization is an essential technique for deploying models on resource-constrained devices. However, its impact on model perceptual fields, particularly regarding class activation maps (CAMs), remains a significant area of investigation. In this study, we explore how quantization alters the spatial recognition ability of the perceptual field of vision models, shedding light on the alignment between CAMs and visual saliency maps across various architectures. Leveraging a dataset of 10,000 images from ImageNet, we rigorously …

abstract arxiv change class cs.cv devices effects explore fields however impact investigation maps network networks neural network neural networks perception quantization study type vision vision models