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DICTA
2009
15 years 8 months ago
SIFTing the Relevant from the Irrelevant: Automatically Detecting Objects in Training Images
Many state-of-the-art object recognition systems rely on identifying the location of objects in images, in order to better learn its visual attributes. In this paper, we propose fo...
Edmond Zhang, Michael Mayo
CORR
2006
Springer
118views Education» more  CORR 2006»
15 years 6 months ago
Minimally Invasive Randomization for Collecting Unbiased Preferences from Clickthrough Logs
Clickthrough data is a particularly inexpensive and plentiful resource to obtain implicit relevance feedback for improving and personalizing search engines. However, it is well kn...
Filip Radlinski, Thorsten Joachims
IJET
2007
99views more  IJET 2007»
15 years 6 months ago
Treating metadata as annotations: separating the content markup from the content
— The use of digital learning resources creates an increasing need for semantic metadata, describing the whole resource, as well as parts of resources. Traditionally, schemas suc...
Fredrik Paulsson, Jonas Engman
CE
2007
104views more  CE 2007»
15 years 6 months ago
The distance from isolation: Why communities are the logical conclusion in e-learning
This paper argues that the internet is built around key technology design features of openness, robustness and decentralisation. These design features have transformed into social...
Martin Weller
RAS
2008
123views more  RAS 2008»
15 years 6 months ago
Fusion of aerial images and sensor data from a ground vehicle for improved semantic mapping
This work investigates the use of semantic information to link ground level occupancy maps and aerial images. A ground level semantic map, which shows open ground and indicates th...
Martin Persson, Tom Duckett, Achim J. Lilienthal