This project demonstrates how to use an Autoencoder for image reconstruction on the CIFAR-10 dataset. It utilizes TensorFlow and Keras to implement the Autoencoder architecture. The project supports ...

Three autoencoder are used for this research work Simple autoencoder, Deep autoencoder and Convolutional autoencoder. To reduced search indexing time, for extracting similar images from the dataset we ...

At 1 sample per pixel (spp), the Monte Carlo integration of indirect illumination results in very noisy images, and the problem can therefore be framed as reconstruction instead of denoising. Previous ...

The quality of the image is very important in image processing. Image blurring is a most common issue, which caused to reduce the quality of the image. Blurred images often occur due to camera shake, ...

Sun, Y., Xue, B., Zhang, M. and Yen, G.G. (2019) A Particle Swarm Optimization-Based Flexible Convolutional Autoencoder for Image Classification. IEEE Transactions on ...

Contribute to shTayefi/Autoencoder-Image-compression-simple- development by creating an account on GitHub. Skip to content. Navigation Menu Toggle navigation. Sign in Product GitHub Copilot. Write ...