This paper reviews the current state of the art in artificial intelligence (AI) technologies and
applications in the context of the creative industries. A brief background of AI, and …

Exabytes of data are generated daily by humans, leading to the growing needs for new
efforts in dealing with the grand challenges for multi-label learning brought by big data. For …

Multi-label image classification is the task of predicting a set of labels corresponding to
objects, attributes or other entities present in an image. In this work we propose the …

The task of multi-label image recognition is to predict a set of object labels that present in an
image. As objects normally co-occur in an image, it is desirable to model the label …

The field of medical diagnostics contains a wealth of challenges which closely resemble
classical machine learning problems; practical constraints, however, complicate the …

The simultaneous recognition of multiple objects in one image remains a challenging task,
spanning multiple events in the recognition field such as various object scales, inconsistent …

Visual attention has become a popular and widely used component for image recognition.
Although various attention-based methods have been proposed and achieved relatively …

For many computer vision applications, such as image description and human identification
recognizing the visual attributes of humans is an essential yet challenging problem. Its …

Multi-label image and video classification are fundamental yet challenging tasks in computer
vision. The main challenges lie in capturing spatial or temporal dependencies between …

Multi-label image recognition is a practical and challenging task compared to single-label
image classification. However, previous works may be suboptimal because of a great …