|
You are here |
blog.demofox.org | ||
| | | | |
thegraphicsblog.com
|
|
| | | | | Sampling is the bane of computer graphics. Aliasing, accuracy, and noise must all be traded off against each other. A sampling method that works well for low sample counts might be inferior at high sample counts. As an example of the sort of problem sampling is meant to solve, take this simple grid: None of... | |
| | | | |
momentsingraphics.de
|
|
| | | | | ||
| | | | |
www.chrisritchie.org
|
|
| | | | | [AI summary] The user is sharing a detailed exploration of graphics processing techniques, including edge detection, median filters, and histogram adjustments. They mention experimenting with different algorithms to enhance image details and reduce noise, as well as using Java for implementing these effects. The post also references related content on thumbnailing, parallelism, and fractal generation, highlighting a focus on both practical coding and artistic effects in graphics programming. | |
| | | | |
blog.keras.io
|
|
| | | [AI summary] The text discusses various types of autoencoders and their applications. It starts with basic autoencoders, then moves to sparse autoencoders, deep autoencoders, and sequence-to-sequence autoencoders. The text also covers variational autoencoders (VAEs), explaining their structure and training process. It includes code examples for each type of autoencoder and mentions the use of tools like TensorBoard for visualization. The VAE section highlights how to generate new data samples and visualize the latent space. The text concludes with references and a note about the potential for further topics. | ||