Few-shot learning has received increasing attention and witnessed significant advances in recent years. However, most of the few-shot methods focus on optimization training process, metric sample generating networks. They ignore importance ground-truth feature distributions classes. This paper proposes a direction-driven weighting method to make classes precisely fit distributions. The learned ...

Combined with weight of samples and kernel function, fuzzy clustering method with generalized entropy is studied. Objective function for fuzzy clustering with generalized entropy based on sample weighting is obtained. Following that, fuzzy clustering algorithm with generalized entropy based on sample weighting is presented. In addition, by introducing kernel into the presented objective functio...

Data-driven speech enhancement (Fingscheidt and Suhadi [1]) aims at improving speech quality for voice calls in a specific noise environment. The essence of the method are a set of frequencydependent weighting rules, indexed by a priori and a posteriori SNRs, which are learned from clean speech and background noise training data. The weighting rules must be stored for each frequency bin separat...

This paper is concerned with the problem of design and implementation a robust adaptive control strategy for flexible joint electrically driven robots (FJEDR), while considering to the constraints on the actuator voltage input. The control design procedure is based on function approximation technique, to avoid saturation besides being robust against both structured and unstructured uncertaintie...

We generalize the Allais common consequence effect by describing three common consequence effect conditions and characterizing their implications for the probability weighting function in rank-dependent expected utility. The three conditions—horizontal, vertical, and diagonal shifts within the probability triangle—are necessary and sufficient for different curvature properties of the probabilit...

Although the depth-of-focus (DOF) has been investigated separately in the central retina and in the near retinal periphery, knowledge about their combined relative contribution to overall blur perception has remained unknown. In the present study, the DOF was measured psychophysically with a naturalistic pictorial stimulus as a function of spatial extent across the near retinal periphery under ...

Optimizing weighting factors for a linear combination of terms in a scoring function is a crucial step for success in developing a threading algorithm. Usually weighting factors are optimized to yield the highest success rate on a training dataset, and the determined constant values for the weighting factors are used for any target sequence. Here we explore completely different approaches to ha...