IEEE SPL Article

Zero-shot learning (ZSL) has enjoyed great popularity in recent years due to its ability to recognize novel objects, where semantic information is exploited to build up relations among different categories. Traditional ZSL approaches usually focus on learning more robust visual-semantic embeddings among seen classes and directly apply them to the unseen classes without considering whether they are suitable.

This letter proposes a new approach to nonnegative Tucker decomposition, which assumes recursive updates of latent factors with any nonnegative matrix factorization algorithm. The proposed strategy is extended to the nonnegatively constrained hierarchical Tucker decomposition model.

A novel method is proposed to construct arbitrary length perfect integer sequences based on all-pass polynomial. It uses a fact that associative sequence of an all-pass polynomial is guaranteed to be perfect. In addition, geometric series method is our special case.

Epochs are the instants of significant excitation to vocal tract system. Existing methods can extract epochs accurately from clean speech signals. However, identification of epoch locations from band-limited telephonic speech is challenging due to the attenuation of fundamental frequency component and degradation caused by channel effect. 

In many applications, different populations are compared using data that are sampled in a biased manner. Under sampling biases, standard methods that estimate the difference between the population means yield unreliable inferences.

Effectively utilizing the common information in a set of video frames is a vital aspect in video segmentation. However, existing methods that transport the common information from a prior frame to the current frame do not make use of the common information effectively.

Existing forensic techniques for image manipulation localization crucially assume that probe pixels belong to one of exactly two classes, genuine or manipulated. This letter argues that this convention fuels mis-labeling particularly in unsupervised settings, where singular but genuine...

In smart metering systems, a rechargeable battery can be utilized to protect the privacy of a user from the utility provider by partially masking the load profile of the user. In this line of research on using rechargeable batteries for privacy protection, most existing works have studied only single-user systems using rechargeable batteries. 

This letter investigates how to place the received-signal-strength (RSS) sensors to improve the static target localization accuracy in the three-dimensional (3-D) space. By using the A-optimality criterion, i.e., minimizing the trace of the inverse Fisher information matrix (FIM), a new optimal RSS sensor placement strategy is developed when sensors can be placed freely in the 3-D space.

In this letter, we consider the problem of direction-of-arrival (DOA) estimation with one-bit quantized array measurements. With analysis, it is shown that, under mild conditions the one-bit covariance matrix can be approximated by the sum of a scaled unquantized covariance matrix and a scaled identity matrix.