We develop a set of methods to improve on the results of self-supervised learning using context. We start with a baseline of patch based arrangement context learning and go from there. Our methods address some overt problems such as chromatic aberration as well as other potential problems such as spatial skew and mid-level feature neglect. We prevent problems with testing generalization on comm...

A context-based spelling error is a spelling or typing error that turns an intended word into another word of the language. For example, the intended word “sight” might become the word “site.” A spell checker cannot identify such an error. In the English language— the case of interest here—a syntax checker may also fail to catch such an error since, among other reasons, the parts-of-speech of a...

In this paper architecture of hybrid control system of robot based on context and learning by natural language is suggested.

I believe that context's ability to reduce the ambiguity of an input signal makes it a vital constraint for understanding the real world. I specifically examine the role of context in vision and how a model-based approach can aid visual search and recognition. Through the implementation of a system capable of learning visual context models from an image database, I demonstrate the utility of th...

This paper proposes a new metric, called Context Based Covariance, to capture contextual information intrinsic to multivariate data. Based on this concept, a minimum distance classifier is designed, and its applicability to the domain of supervised machine learning is discussed. The performance of the proposed metric is compared with conventional minimum distance classifiers based on Mahalanobi...

Practicing retrieval is a powerful way to promote learning and long-term retention. This chapter addresses the theoretical underpinnings of retrieval-based learning. We review methodological issues in retrieval practice research, identify key findings to be Psychology of Learning and Motivation, Volume 61 # 2014 Elsevier Inc. ISSN 0079-7421 All rights reserved. http://dx.doi.org/10.1016/B978-0-...

To be effective, a learning process must be adapted to the learner’s context. Such a context should be described at least from pedagogical, technological and learning perspectives. Current e-Learning approaches either fail to provide learning experiences within rich contexts, thus hampering the learning process, or provide extremely contextualized content that is highly coupled with context inf...

Accretion-based Ontology Learner (ACOL) is a ontology learner within the SAGO framework. It accumulates evidence that contributes to each relationship between concepts picked up by the ontology learner. This means that, instead of having a fixed relationship between concepts, ACOL retains the evidence about the relationships and calculates, or resolves, the relationship according to a given con...

Context aware E-Learning systems provide learning content according to a learner’s context. In the existing context aware E-Learning systems there is no standardized set of context parameters considered and content is adapted based on a randomly considered set of parameters. In this work, a standardization of context model for context aware E-learning has been proposed. The design of the standa...