To solve this problem, we propose a new layered image compression framework with encoder-decoder matched semantic segmentation (EDMS). And then, followed by the semantic segmentation, a special ...

In this article, we are going to see how we can remove noise from the image data using an encoder-decoder model. Having clear and processed images or videos is very important in any computer vision ...

This repository contains the implementation of an Encoder-Decoder model for image denoising using the MNIST dataset. The model is trained with varying levels of Gaussian noise and bottleneck ...

Abstract: Image compression, which aims to represent an image with less storage space, is a classical problem in image processing. Recently, by training an encoder-quantizer-decoder network, deep ...

This project is a simple implementation of auto-encoder neural network for image compression. The auto-encoder neural network is trained on the ImageNet dataset. The trained model is then used to ...

Along with the rise of the modern World Wide Web came the introduction of the JPEG image compression standard ... improve JPEG with Jpegli, a new encoder and decoder library that promises to ...

Engineered at intoPIX, TicoRAW is an innovative, lossless quality, low-power, low-memory and line-based image processing and compression technology created to unleash image sensor dataflows. TicoRAW ...