Metric learning aims to measure the similarity among samples while using an optimal
distance metric for learning tasks. Metric learning methods, which generally use a linear …

Although image inpainting, or the art of repairing the old and deteriorated images, has been
around for many years, it has recently gained even more popularity, because of the recent …

The content based image retrieval aims to find the similar images from a large scale dataset
against a query image. Generally, the similarity between the representative features of the …

We propose in this paper a novel model-based gait recognition method, PoseGait. Gait
recognition is a challenging and attractive task in biometrics. Early approaches to gait …

Most existing approaches address multi-view subspace clustering problem by constructing
the affinity matrix on each view separately and afterwards propose how to extend spectral …

Of late, neural networks and Multiple Instance Learning (MIL) are both attractive topics in the
research areas related to Artificial Intelligence. Deep neural networks have achieved great …

With the development of web technology, multi-modal or multi-view data has surged as a
major stream for big data, where each modal/view encodes individual property of data …

Semantic relation extraction is crucial to automatically constructing a knowledge graph (KG),
and it supports a variety of downstream natural language processing (NLP) tasks such as …

Image classification has been widely adopted by current social media applications.
Compared with fully supervised classification, semisupervised classification attracts more …

Entity and relation extraction is a task that combines detecting entity mentions and
recognizing entities' semantic relationships from unstructured text. We propose a hybrid …