| |
---|
| | |
---|
| | <h4>M. Winikoff</h4> |
---|
| | |
---|
| | <p>In this paper we consider the broader issue of gaining assurance that an agent system will behave appropriately when it is deployed. We ask to what extent this problem is addressed by existing research into formal verification. We identify a range of issues with existing work which leads us to conclude that, broadly speaking, verification approaches on their own are too narrowly focussed. We argue that a shift in direction is needed, and outline some possibilities for such a shift in direction.</p> |
---|
| | |
---|
| | <link rel="Stylesheet" href="DPSstyles.css" type="text/css"> |
---|
| | |
---|
| | <p><a href="papers/dp2010-01.pdf">Download</a> (PDF, 296 KB)</p> |
---|
| | |
---|
| | <hr> |
---|
| |
---|
| | <p>Novelty detection is an important functionality that has found many applications in information retrieval and processing. In this paper we propose a novel framework that deals with novelty detection for multiple-scene image sets. Working with wildlife image data, the framework starts with image segmentation, followed by feature extraction and classification of the image blocks extracted from image segments. The labelled image blocks are then scanned through to generate a co-occurrence matrix of object labels, representing the semantic context within the scene. The semantic co-occurrence matrices then undergo binarization and principal component analysis for dimension reduction, forming the basis for constructing one-class models for each scene category. An algorithm for outlier detection that employs multiple one-class models is proposed. An advantage of our approach is that it can be used for scene classification and novelty detection at the same time. Our experiments show that the proposed approach algorithm gives favourable performance for the task of detecting novel wildlife scenes, and binarization of the label co-occurrence matrices helps to significantly increase the robustness in dealing with the variation of scene statistics.</p> |
---|
| | |
---|
| | <p><strong>Keywords:</strong> context, co-occurrence matrix, semantics, novel image, multi-class</p> |
---|
| | |
---|
| | <p><a href="papers/dp2010-02.pdf">Download</a> (PDF, 3.2 MB)</p> |
---|
| | <p class="note">Corrected version uploaded 2010-05-04.</p> |
---|
| | |
---|
| | <p><a href="papers/dp2010-02.pdf">Download</a> (PDF, 3.4 MB)</p> |
---|
| | |
---|
| | <hr> |
---|
| | |
---|
| | <a name="dp2010-03"></a><h3>2010/03: Norm identification in multi-agent societies</h3> |
---|
| | |
---|
| |
---|
|