We propose an end-to-end place recognition model based on a novel deep neural network.
First, we propose to exploit the spatial pyramid structure of the images to enhance the vector …

In recent years, the advances in data collection and statistical analysis promotes canonical
correlation analysis (CCA) available for more advanced research. CCA is the main …

With the advent of Internet and computing, we entered into an era with more people
exchanging information over the Internet using devices like desktops, laptops, tablets …

In this work, travel destinations and business locations are taken as venues. Discovering a
venue by a photograph is very important for visual context-aware applications …

The weight-adapted convolution neural network (WACNN) is proposed to extract
discriminative expression representations for recognizing facial expression. It aims to make …

Eddy current testing (ECT) has been employed as a traditional non-destructive testing and
evaluation (NDT&E) tool for many years. It has developed from single frequency to multiple …

Latent variable-based process monitoring (PM) models have been generously developed by
shallow learning approaches, such as multivariate statistical analysis and kernel techniques …

Quality prediction is beneficial to intelligent inspection, advanced process control, operation
optimization, and product quality improvements of complex industrial processes. Most of the …

Multi-task learning plays an important role in face multi-attribute prediction. At present, most
researches excavate the shared information between attributes by sharing all convolutional …

Data-driven techniques such as principal component analysis (PCA) have been widely used
to derive predictive models from historical data and applied for quality prediction in industry …