Image Quantization

Image quantization aims to represent images using fewer bits, reducing storage and computational costs while preserving image quality or model performance. Current research focuses on improving quantization techniques for various deep learning models, including object detectors, generative models like VQGAN, and large language models, often employing methods like quantization-aware training and mixed-precision quantization to mitigate performance degradation. These advancements are crucial for deploying complex models on resource-constrained devices and improving the efficiency of large-scale machine learning applications, impacting fields ranging from computer vision to natural language processing.