Time Series Classification and Extrinsic Regression are important and challenging machine
learning tasks. Deep learning has revolutionized natural language processing and computer …

The emergence of new technologies has changed the way clinicians perform diagnosis.
Medical imaging play a crucial role in this process, given the amount of information that they …

As a widely-used method in the image categorization tasks, the Bag-of-Words (BoW) method
still suffers from many limitations such as overlooking spatial information. In this paper, we …

In the Australian construction industry, effective supply chain risk management (SCRM) is
critical due to its complex networks and susceptibility to various risks. This study explores the …

Automatic image annotation plays a significant role in image understanding, retrieval,
classification, and indexing. Today, it is becoming increasingly important in order to annotate …

Refining image annotation has become one of the core research topics in computer vision
and pattern recognition due to its great potentials in image retrieval. However, it is still in its …

Traditional methods of automatic generation of recruitment text usually rely on a large
number of data annotation and complex statistical algorithms, but these methods have …

In the era of continuous development of computer technology, the application of artificial
intelligence (AI) and big data is becoming more and more extensive. With the help of …

Image annotation has been an active research in computer vision. Most of the prior research
works focus on annotating images with fixed number of labels, while it is unreasonable to …

Image captioning models successfully describe the visual contents of images using natural
language. To generate more natural and diverse descriptions, a model must learn style …