Multi-view visual classification methods have been widely applied to use discriminative
information of different views. This strategy has been proven very effective by many …

Objective. This paper proposes a novel simultaneous and proportional multiple degree of
freedom (DOF) myoelectric control method for active prostheses. Approach. The approach is …

Recently, many methods based on low-rank representation have been proposed for fabric
defect detection. Most of them relax the low-rank decomposition problem to a nuclear norm …

Supervised methods have been widely used for image classifications. Although great
progress has been made, existing supervised methods rely on well-labeled samples for …

This paper tries to separate fine-grained images by jointly learning the encoding parameters
and codebooks through low-rank sparse coding (LRSC) with general and class-specific …

Pairwise similarity has been widely used for image classification by propagating the class
information from labeled images to unlabeled images and predicting the classes of …

Fine-grained image classification attempts to accurately classify images that are similar to
each other. Multiview information is often used to improve the classification accuracy …

Most image classification methods are designed to either boost the classification accuracies
with abundant supervision, or cope with the shortage of supervision information. This is often …

Accurately classifying images using few-shot samples have been widely explored by
researchers. However, these methods have two drawbacks. First, images are often used …

Sparsity prior is a powerful tool for compressive sensing reconstruction (CSR) of
hyperspectral image (HSI). However, conventional HSI-CSR strategies are not tuned to …