Semantic segmentation is a challenging task in computer vision. In recent years, the
performance of semantic segmentation has been greatly improved by using deep learning …

Deep learning, which is a subfield of machine learning, has opened a new era for the
development of neural networks. The auto-encoder is a key component of deep structure …

In this paper, we review the background and state-of-the-art of big data. We first introduce
the general background of big data and review related technologies, such as could …

Recent technological advancements have led to a deluge of data from distinctive domains
(eg, health care and scientific sensors, user-generated data, Internet and financial …

Where previous reviews on content-based image retrieval emphasize what can be seen in
an image to bridge the semantic gap, this survey considers what people tag about an image …

Sparse representation (or coding)-based classification (SRC) has gained great success in
face recognition in recent years. However, SRC emphasizes the sparsity too much and …

We propose a single image dehazing method that is based on a physical model and the
dark channel prior principle. The selection of an atmospheric light value is directly …

By embedding prior knowledge into the learning structure, this paper presents a two-step
semi-supervised learning method called fuzzy deep belief networks (FDBN) for sentiment …

Recently, tag recommendation (TR) has become a very hot research topic in data mining
and related areas. However, neither co-occurrence based methods which only use the item …

The ever-increasing amount of multimedia content on modern social media platforms are
valuable in many applications. While the openness and convenience features of social …