Face-pose estimation aims at estimating the gazing direction with two-dimensional face
images. It gives important communicative information and visual saliency. However, it is …

In recent years, deep learning has been proved to be a promising bearing fault diagnosis
technology. However, most of the existing methods are based on single-task learning. Fault …

Accurate and real-time fault diagnosis (FD) and working conditions identification (WCI) are
the key to ensuring the safe operation of mechanical systems. We observe that there is a …

Deep domain adaptation methods have achieved appealing performance by learning
transferable representations from a well-labeled source domain to a different but related …

We present an end-to-end head-pose estimation network designed to predict Euler angles
through the full range head yaws from a single RGB image. Existing methods perform well …

Clustering is an important technique to deal with large scale data which are explosively
created in internet. Most data are high-dimensional with a lot of noise, which brings great …

Multi-trait and multi-environment data are common in animal and plant breeding programs.
However, what is lacking are more powerful statistical models that can exploit the correlation …

In this paper we propose ResnetCrowd, a deep residual architecture for simultaneous crowd
counting, violent behaviour detection and crowd density level classification. To train and …

Multi-target regression has recently regained great popularity due to its capability of
simultaneously learning multiple relevant regression tasks and its wide applications in data …

Depth cameras allow to set up reliable solutions for people monitoring and behavior
understanding, especially when unstable or poor illumination conditions make unusable …