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» Visual explanations of probabilistic reasoning
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NIPS
2004
13 years 6 months ago
Maximising Sensitivity in a Spiking Network
We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...
Anthony J. Bell, Lucas C. Parra
IROS
2007
IEEE
175views Robotics» more  IROS 2007»
13 years 11 months ago
Simulation and weights of multiple cues for robust object recognition
Reliable recognition of objects is an important capabaility in the progress towards getting agents to accomplish and assist in a variety of useful tasks such as search and rescue ...
Sarah Aboutalib, Manuela M. Veloso
GIS
2005
ACM
14 years 6 months ago
In-network surface simplification for sensor fields
Recent research literature on sensor network databases has focused on finding ways to perform in-network aggregation of sensor readings to reduce the message cost. However, with t...
Brian Harrington, Yan Huang
IROS
2008
IEEE
238views Robotics» more  IROS 2008»
13 years 12 months ago
Shape-guided superpixel grouping for trail detection and tracking
Abstract— We describe a framework for detecting and tracking continuous ”trails” in images and image sequences for autonomous robot navigation. Continuous trails are extended...
Christopher Rasmussen, Donald Scott
MM
2009
ACM
203views Multimedia» more  MM 2009»
13 years 10 months ago
Distance metric learning from uncertain side information with application to automated photo tagging
Automated photo tagging is essential to make massive unlabeled photos searchable by text search engines. Conventional image annotation approaches, though working reasonably well o...
Lei Wu, Steven C. H. Hoi, Rong Jin, Jianke Zhu, Ne...