• Publications
  • Influence
Modeling and assessment of combined GPS/GLONASS precise point positioning
A combination of GPS and GLONASS observations can offer improved reliability, availability and accuracy for precise point positioning (PPP). Expand
MaskReID: A Mask Based Deep Ranking Neural Network for Person Re-identification
We propose a novel mask based deep ranking neural network with a skipped fusing layer for person Re-ID. Expand
Precise Point Positioning Using Combined GPS and GLONASS Observations
Precise Point Positioning (PPP) is currently based on the processing of only GPS observations. Its positioning accuracy, availability and reliability are very dependent on the number of visibleExpand
WebCaricature: a benchmark for caricature recognition
A new caricature dataset is built, with a much greater number of available images, artistic styles and larger intra-personal variations for caricature recognition. Expand
Adaptive grid job scheduling with genetic algorithms
This paper proposes two models for predicting the completion time of jobs in a service Grid that use the predictive models to schedule jobs at both system level and application level. Expand
Real-Time Abnormal Event Detection in Complicated Scenes
We proposed a novel real-time abnormal event detection framework that requires a short training period and has a fast processing speed. Expand
Multimodal Sparse Representation-Based Classification for Lung Needle Biopsy Images
A novel method, multimodal sparse representation-based classification (mSRC), is proposed for classifying lung needle biopsy images. Expand
A Combined GPS/GLONASS Navigation Algorithm for use with Limited Satellite Visibility
Navigation users will significantly benefit from the combined use of GPS and GLONASS due to the improved reliability, availability and accuracy especially in an environment with limited satelliteExpand
WebCaricature: a benchmark for caricature face recognition
We have collected and set up a dataset of caricatures to promote and facilitate the study of caricature face recognition. Expand
Self-paced dictionary learning for image classification
We propose a self-paced dictionary learning algorithm in order to accommodate the "hidden" information of the samples into the learning procedure, which uses the easy samples to train the dictionary first, and iteratively introduces more complex samples in the remaining training procedure until the entire training data are all easy samples. Expand