Deeplearing, Computer Vision, Streamlit App Deployment, Tf Data.
approximating a neural network that uses floating-point numbers by a neural network of low bit width numbers. This dramatically reduces both the memory requirement and computational cost of using neural networks. After quantization the size of the DNCNN model is reduced from 7 MB to 2 MB and RIDNET