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TMI
1998
140views more  TMI 1998»
13 years 7 months ago
Automated Seeded Lesion Segmentation on Digital Mammograms
Abstract—Segmenting lesions is a vital step in many computerized mass-detection schemes for digital (or digitized) mammograms. We have developed two novel lesion segmentation tec...
Matthew A. Kupinski, Maryellen L. Giger
JUCS
2010
116views more  JUCS 2010»
13 years 6 months ago
Content Recommendation in APOSDLE using the Associative Network
: One of the success factors of Work Integrated Learning (WIL) is to provide the appropriate content to the users, both suitable for the topics they are currently working on, and t...
Hermann Stern, Rene Kaiser, Philip Hofmair, Peter ...
ICCAD
2009
IEEE
119views Hardware» more  ICCAD 2009»
13 years 5 months ago
Iterative layering: Optimizing arithmetic circuits by structuring the information flow
Current logic synthesis techniques are ineffective for arithmetic circuits. They perform poorly for XOR-dominated circuits, and those with a high fan-in dependency between inputs ...
Ajay K. Verma, Philip Brisk, Paolo Ienne
CVPR
2012
IEEE
11 years 10 months ago
Unsupervised feature learning framework for no-reference image quality assessment
In this paper, we present an efficient general-purpose objective no-reference (NR) image quality assessment (IQA) framework based on unsupervised feature learning. The goal is to...
Peng Ye, Jayant Kumar, Le Kang, David S. Doermann
WIAS
2008
128views more  WIAS 2008»
13 years 8 months ago
Considering operational issues for multiagent conceptual inferencing in a distributed information retrieval application
Our system, based on a multiagent framework called collaborative understanding of distributed knowledge (CUDK), is designed with the overall goal of balancing agents' conceptu...
Leen-Kiat Soh