A growing body of evidence currently proposes that deep learning approaches can serve as
an essential cornerstone for the diagnosis and prediction of Alzheimer's disease (AD). In …

Correlation filters take advantage of specific properties in the Fourier domain allowing them
to be estimated efficiently: O (ND log D) in the frequency domain, versus O (D^ 3+ ND^ 2) …

Sparse coding has become an increasingly popular method in learning and vision for a
variety of classification, reconstruction and coding tasks. The canonical approach …

We investigate the problem of estimating the 3D shape of an object defined by a set of 3D
landmarks, given their 2D correspondences in a single image. A successful approach to …

Low rank models have been widely used for the representation of shape, appearance or
motion in computer vision problems. Traditional approaches to fit low rank models make use …

The success of research on matrix completion is evident in a variety of real-world
applications. Tensor completion, which is a high-order extension of matrix completion, has …

Abstract Binary Neural Networks (BNNs) show great promise for real-world embedded
devices. As one of the critical steps to achieve a powerful BNN, the scale factor calculation …

We investigate the problem of estimating the 3D shape of an object, given a set of 2D
landmarks in a single image. To alleviate the reconstruction ambiguity, a widely-used …

In this paper, we study the problem of unifying knowledge from a set of classifiers with
different architectures and target classes into a single classifier, given only a generic set of …

Fingerprinting based indoor positioning system is gaining more research interest under the
umbrella of location-based services. However, existing works have certain limitations in …