Face image quality can be defined as a measure of the utility of a face image to automatic face recognition. In this work, we propose (and compare) two methods for learning face image quality based on target face quality values from (i) human assessments of face image quality (matcher-independent), and (ii) quality values computed from similarity scores (matcherdependent). A support vector regr...

Speakers often tailor their utterances to the needs of particular addressees--a process called audience design. We argue that important aspects of audience design can be understood as emergent features of ordinary memory processes. This perspective contrasts with earlier views that presume special processes or representations. To support our account, we present a study in which Directors engage...

A novel minutia-based fingerprint matching algorithm is proposed that employs iterative global alignment on two minutia sets. The matcher considers all possible minutia pairings and iteratively aligns the two sets until the number of minutia pairs does not exceed the maximum number of allowable oneto-one pairings. The optimal alignment parameters are derived analytically via linear least square...

One of the most important roles in the machine learning area is to classify, and neural networks are very important classifiers. However, traditional neural networks cannot identify intervals, let alone classify them. To improve their identification ability, we propose a neural network-based interval matcher in our paper. After summarizing the theoretical construction of the model, we take a si...

In this paper we present SEMA tool for the automatic mapping of ontologies. The main purpose of SEMA is to locate one to one equivalence correspondences (mappings) between elements (i.e., classes and properties) of two input ontologies. Towards this goal, SEMA synthesizes lexical, semantic and structural matching algorithms through their iterative execution. 1 Presentation of the system 1.1 Sta...

We present an algorithm for identity verification using only information from the hair. Face recognition in the wild (i.e., unconstrained settings) is highly useful in a variety of applications, but performance suffers due to many factors, e.g., obscured face, lighting variation, extreme pose angle, and expression. It is well known that humans utilize hair for identification under many of these...

Spatial and temporal modeling is one of the most core aspects few-shot action recognition. Most previous works mainly focus on long-term relation based high-level spatial representations, without considering crucial low-level features short-term relations. Actually, former feature could bring rich local semantic information, latter represent motion characteristics adjacent frames, respectively....