To flexibly and robustly handle diverse problems, AI systems can leverage dual-process theories of human cognition that ...

The 330 million parameter model was trained using Azure’s A100 GPUs and fine-tuned through a multi-phase process.

It features an HFFIbased dual network encoder, a dual-path decoder, an enhanced multi-scale attention mechanism (EMSA), and an innovative Multivariate Matching method, forming an efficient maritime ...

Automatic medical image segmentation has made great progress owing to powerful deep representation learning. Inspired by the success of self-attention mechanism in transformer, considerable efforts ...

The original transformer architecture consists of two main components: an encoder and a decoder. The encoder processes the input sequence and generates a contextualized representation, which is then ...