Abstract: In this article, a stochastic recurrent encoder decoder neural network (SREDNN), which considers latent random variables in its recurrent structures, is developed for the first time for the ...

High level API to define cell/nuclei instance segmentation models. 6 cell/nuclei instance segmentation model architectures Flexibility to modify the components of the model architectures. Sliding ...

Abstract: This paper proposes a GeneraLIst encoder-Decoder (GLID) pre-training method for better handling various downstream computer vision tasks. While self-supervised pre-training approaches, e.g., ...

Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to ...

A PyTorch implementation of the hierarchical encoder-decoder architecture (HRED) introduced in Sordoni et al (2015). It is a hierarchical encoder-decoder architecture for modeling conversation triples ...

Nowadays, computer programs can translate text from one language to another using a process known as machine translation (MT), sometimes known as automated translation. MT uses a machine translation ...

Machine learning (ML) model developers frequently start with a basic backbone model that has been trained at scale and can be applied to a variety of downstream applications. Several popular backbone ...

Dr. James McCaffrey of Microsoft Research details the "Hello World" of image classification: a convolutional neural network (CNN) applied to the MNIST digits dataset. The "Hello World" of image ...