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CVBIA
2005
Springer
14 years 1 months ago
Segmenting Brain Tumors with Conditional Random Fields and Support Vector Machines
Abstract. Markov Random Fields (MRFs) are a popular and wellmotivated model for many medical image processing tasks such as segmentation. Discriminative Random Fields (DRFs), a dis...
Chi-Hoon Lee, Mark Schmidt, Albert Murtha, Aalo Bi...
ROBOCOMM
2007
IEEE
14 years 2 months ago
Path planning using Shi and Karl level sets
—Path planning for mobile robots is a well researched problem for over three decades. In this paper, we test and evaluate a new approach based on Shi and Karl Level Sets for mobi...
Randeep Singh, Nagaraju Bussa
ICASSP
2008
IEEE
14 years 2 months ago
Nested support vector machines
The one-class and cost-sensitive support vector machines (SVMs) are state-of-the-art machine learning methods for estimating density level sets and solving weighted classificatio...
Gyemin Lee, Clayton Scott
ICRA
2002
IEEE
111views Robotics» more  ICRA 2002»
14 years 29 days ago
Mission Planning for the Sun-Synchronous Navigation Field Experiment
This paper describes TEMPEST, a planner that enables a solar-powered rover to reason about path selection and event placement in terms of available solar energy and anticipated po...
Paul Tompkins, Anthony Stentz, William Whittaker
CDC
2009
IEEE
148views Control Systems» more  CDC 2009»
14 years 22 hour ago
An adaptive artificial potential function approach for geometric sensing
In this paper, a novel artificial potential function is proposed for planning the path of a robotic sensor in a partially observed environment containing multiple obstacles and mul...
Guoxian Zhang, Silvia Ferrari