Attributes are descriptive characteristics with crosscategory applicability. They can be used to provide additional information that is not found in simple object classification, giving the computer a complete picture of the item and the state in which it appears. While attribute prediction has been studied extensively in still images, this is not the case in videos. However, there exist visual...

This paper addresses the opportunities for, and eeects of, incorporating object attributes in Linda-like tuple-space systems. The focus is on exploring how the coordination attributes are aaected by this enhancement, and investigating in what ways the classical Linda model needs to be modiied. Particular emphasis is placed on the potential practical gains to be expected in both performance and ...

Traditional active learning allows a (machine) learner to query the (human) teacher for labels on examples it finds confusing. The teacher then provides a label for only that instance. This is quite restrictive. In this paper, we propose a learning paradigm in which the learner communicates its belief (i.e. predicted label) about the actively chosen example to the teacher. The teacher then conf...

Automated person re-identification using only visual information from public-space CCTV video is challenging for many reasons, such as poor resolution or challenges involved in dealing with camera calibration. More critical still, the majority of clothing worn in public spaces tends to be non-discriminative and therefore of limited disambiguation value. Most re-identification techniques develop...

We consider the task of acquisition of terminological knowledge from given assertional data. However, when evaluating data of realworld applications we often encounter situations where it is impractical to deduce only crisp knowledge, due to the presence of exceptions or errors. It is rather appropriate to allow for degrees of uncertainty within the derived knowledge. Consequently, suitable met...

to identify important attributes/factors that contribute to grain and biological yields of wheat, 9912 sets of diverse data from field studies were extracted, and supervised attribute-weighting models were employed. results showed that when biological yield was the output, grain yield, nitrogen applied, rainfall, irrigation regime, and organic content were the most important factors/attributes,...