Context-Aware Superpixel and Bilateral Entropy—Image Coherence Induces Less Entropy

Superpixel Convolutional Networks Using Bilateral Inceptions

In this paper we propose a CNN architecture for image segmentation. We introduce a new “bilateral inception” layer that is used on top of a fully convolutional architecture. The bilateral inception performs a filtering between superpixels in an image. This addresses two problems that arise with CNN segmentation architectures. First, this layer propagates label information between (super) pixels...

Context-aware Querying Better Answers with Less Effort

Context-aware systems: concept, functions and applications in digital libraries

Background and Aim Among the places that context-aware systems and services would be very useful, are libraries. The purpose of this study is to achieve a coherent definition of context aware systems and applications, especially in digital libraries. Method: This was a review article that was conducted by using Library method by searching articles and e-books on websites and databases. Results:...

Supplementary Material for Superpixel Convolutional Networks using Bilateral Inceptions

The bilateral inception module presented in the main paper computes a matrixvector product between a Gaussian filter K and a vector of activations zc. Bilateral filtering is an important operation and many algorithmic techniques have been proposed to speed-up this operation [1,2,3]. In the main paper we opted to implement what can be considered the brute-force variant of explicitly constructing...

CAMAC: a context-aware mandatory access control model

Mandatory access control models have traditionally been employed as a robust security mechanism in multilevel security environments such as military domains. In traditional mandatory models, the security classes associated with entities are context-insensitive. However, context-sensitivity of security classes and flexibility of access control mechanisms may be required especially in pervasive c...