Bletchley Community Hospital

A two-year-old domestic shorthair cat presented for investigation of a six-month history of intermittent vomiting, weight loss, hyporexia and lethargy. Abdominal ultrasound was performed and revealed extensive small intestinal wall thickening (average thickness measured 8 mm) with preserved layering. In particular, there was marked thickening of the muscularis propria layer (variable thickness from 4 to 5 mm) with normal mucosal and submucosal layers (Daniaux and others 2014), Overall, there was normal intestinal peristaltic activity and no evidence of intestinal obstruction. The …

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This paper discusses facial recognition as applied to the classification of two-dimensional images and propose a new architecture that allows a fast derivation of compact and invariant features from the Radon space. Our approach has been inspired by the review of feature-based non-connectionist and connectionist models of facial recognition. In the feature based non-connectionist model, a large part of the computational effort is focused on the extraction of facial features or the geometrical encoding of the face and the measurement of statistical parameters to describe their relationship. The connectionist model focuses on two-dimensional intensity values of the facial image allowing the geometrical encoding to be measured implicitly. The connectionist model is thus susceptible to variations in lighting coditions, spatial position and orientation of the images and can result in a poor detection of faces. An additional bottleneck of the connectionist model is the large feature vector size applied to its input that can cause non-convergence problems during traning. The Radon transform is a genetic transformations that is capable of representing shapes and it is used to compute harmonic components from which compact and invariant features can be derived. It is shown in this paper that theses features when applied to a connectionist model result in a system that is capable of achieving high recognition rates and at high significance levels.

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An abstract is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.

An abstract is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.

An abstract is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.