For instance, you could train an autoencoder on grainy images and then use the trained model to remove the grain/noise from the image. Let’s take a look at the architecture of an autoencoder. We’ll ...

Simple Neural Network is feed-forward wherein info information ventures just in one direction.i.e. the information passes from input layers to hidden layers finally to the output layers. Recurrent ...

Explore how Sparc3D transforms 2D images into detailed 3D models with AI-powered efficiency and precision. Discover more.

SHENZHEN, China, Feb. 14, 2025 /PRNewswire/ -- MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, they Announced the ...

The propsoed model architecture is presented for both RGB and Multispectral ... title = {Hybrid Spatial–Spectral Autoencoder Models for Lossy Satellite Image Compression}, journal = {Journal of ...

They can be easily installed via pip or conda. In the notebook folder, one can find the *.ipynb files corresponding to the tutorials to run the models in Google Colab without installing the package.

We propose an adaptive 1D convolutional autoencoder architecture for lossy hyperspectral data compression with the property of portability to unknown spectral signatures of different sensors. In our ...

We propose two different 3D-Hybrid Convolutional Autoencoder models with increased compression rates compared to 1D methods that can compress and reconstruct hyperspectral data with arbitrary spectral ...