The aim of multi-output learning is to simultaneously predict multiple outputs given an input.
It is an important learning problem for decision-making since making decisions in the real …

Methodologies that utilize Deep Learning offer great potential for applications that
automatically attempt to generate captions or descriptions about images and video frames …

It is always well believed that modeling relationships between objects would be helpful for
representing and eventually describing an image. Nevertheless, there has not been …

This survey presents a review of state-of-the-art deep neural network architectures,
algorithms, and systems in speech and vision applications. Recent advances in deep …

Image captioning means automatically generating a caption for an image. As a recently
emerged research area, it is attracting more and more attention. To achieve the goal of …

Abstract Facial Expression Recognition (FER) has long been a challenging task in the field
of computer vision. In this paper, we present a novel model, named Deep Attentive Multi …

Image captioning which automatically generates natural language descriptions for images
has attracted lots of research attentions and there have been substantial progresses with …

In this paper, we propose a novel encoding framework to learn the multi-scale context
information of the visual scene for image captioning task. The devised multi-scale context …

Describing what has changed in a scene can be useful to a user, but only if generated text
focuses on what is semantically relevant. It is thus important to distinguish distractors (eg a …

In recent years, advanced research has focused on the direct learning and analysis of
remote-sensing images using natural language processing (NLP) techniques. The ability to …