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Object Recognition and Active Learning in Microscope Images |
Nugent, Conor; Cunningham, Padraig
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TCD-CS-2006-45 Microscopic analysis forms an integral part of many scientific
studies. It is a task which requires great expertise and care. However, it
can often be an extremely repetitive and laborious task. In some cases
many hundreds of slides may need to analysed, a process that will require
each slide to be meticulously examined. Machine vision tools could be
used to help assist in just such repetitive and tedious tasks. However,
many machine vision solutions involve a lengthy data acquisition phase
and in many cases result in systems that are highly specialised and not
easily adaptable. In this paper, we describe a framework that applies
flexible machine vision techniques to microscope analysis and utilises
active learning to help overcome the data acquisition and adaptability
problems. In particular we investigate the potential of various aspects of
our proposed framework on a particular real world microscopic task, the
recognition of parasite eggs.
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Keyword(s):
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Computer Science |
Publication Date:
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2006 |
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Type:
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Report |
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Peer-Reviewed:
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Unknown |
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Language(s):
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English |
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Institution:
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Trinity College Dublin |
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Citation(s):
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Nugent, Conor; Cunningham, Padraig. 'Object Recognition and Active Learning in Microscope Images'. - Dublin, Trinity College Dublin, Department of Computer Science, TCD-CS-2006-45, 2006, pp10 |
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Publisher(s):
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Trinity College Dublin, Department of Computer Science |
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File Format(s):
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application/pdf |
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First Indexed:
2014-05-13 05:30:59 Last Updated:
2015-04-10 05:13:46 |
