This pressing need sparked a pioneering collaboration between Vodafone’s Innovation & Tech Center in Dresden and Bundesliga ...

Abstract: Developing deep learning models for accurate segmentation of biomedical CT images is challenging due to their complex structures, anatomy variations, noise, and unavailability of sufficient ...

Attention mechanisms, especially in transformer models, have significantly enhanced the performance of encoder-decoder architectures, making them highly effective for a wide range of ...

What Is An Encoder-Decoder Architecture? An encoder-decoder architecture is a powerful tool used in machine learning, specifically for tasks involving sequences like text or speech. It’s like a ...

A hierarchical neural attention encoder uses multiple layers of attention modules to deal with tens of thousands of past inputs. Another kind of deep learning algorithm—not a deep neural network ...

ABSTRACT: In recent years, deep learning has been widely used in the field of image understanding and made breakthroughs research progress in image understanding. Because remote sensing application ...

In 2015, Sequence to Sequence Learning with Neural Network became a very popular architecture and with that the encoder-decoder architecture also became part of wide deep learning community. The paper ...