In the picture below, this property is shown with the ability of the re-trained decoder (g 2) to decode the bitstream generated by the baseline encoder (f 1).

This project implements an AI-powered Image Caption Generator using a Convolutional Neural Network (CNN) as an encoder and an LSTM-based Recurrent Neural Network (RNN) as a decoder.

2.2. Multi-Scale Encoder-Decoder Self-Attention Mechanism As mentioned earlier, by providing two levels of attention mechanisms (global and local attention), we facilitate a deep neural network ...

Automatically generating natural language descriptions of images is a fundamental problem in artificial intelligence that connects computer vision and natural language processing. In recent years ...

Image segmentation is a key technology in remote sensing image interpretation, and it is widely used in many fields. Aiming at the common problems of low segmentation accuracy and blurred target ...

Then, the brain encoder learns to align the MEG signals to those image embeddings. Finally, the image decoder creates a plausible image based on those brain representations.

Resource Contention: The vision encoder is often a compute and memory-intensive task. When processing high-resolution images or performing complex preprocessing, it competes for valuable GPU resources ...