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A Trainable Texture Anomaly Detector Using The Adaptive Cluster Expansion (ace) Method by Stephen P. Luttrell
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1DTIC ADA235346: A Trainable Texture Anomaly Detector Using The Adaptive Cluster Expansion (ACE) Method.
By Defense Technical Information Center
We derive an adaptive hierarchical maximum entropy estimate of probability density functions, whose mathematical structure suggest the name 'adaptive cluster expansion' (ACE). We apply ACE to the problem of locating statistically anomalous regions in otherwise homogeneous textured images, which we demonstrate using several images of Brodatz textures.
“DTIC ADA235346: A Trainable Texture Anomaly Detector Using The Adaptive Cluster Expansion (ACE) Method.” Metadata:
- Title: ➤ DTIC ADA235346: A Trainable Texture Anomaly Detector Using The Adaptive Cluster Expansion (ACE) Method.
- Author: ➤ Defense Technical Information Center
- Language: English
“DTIC ADA235346: A Trainable Texture Anomaly Detector Using The Adaptive Cluster Expansion (ACE) Method.” Subjects and Themes:
- Subjects: ➤ DTIC Archive - Luttrell, Stephen P - ROYAL SIGNALS AND RADAR ESTABLISHMENT MALVERN (UNITED KINGDOM) - *MATHEMATICAL MODELS - DETECTORS - TRAINING - PROBABILITY DENSITY FUNCTIONS - REGIONS - UNITED KINGDOM - IMAGES - ADAPTIVE SYSTEMS - EXPANSION - TEXTURE - HOMOGENEITY - ANOMALIES - CLUSTERING
Edition Identifiers:
- Internet Archive ID: DTIC_ADA235346
Downloads Information:
The book is available for download in "texts" format, the size of the file-s is: 27.03 Mbs, the file-s for this book were downloaded 53 times, the file-s went public at Fri Mar 02 2018.
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