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» Machine Learning, Machine Vision, and the Brain
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ISBI
2006
IEEE
13 years 10 months ago
Improve brain registration using machine learning methods
A machine learning method is introduced here to improve the accuracy of brain registration. Generally, different brain regions might need different types or sets of features for r...
Guorong Wu, Feihu Qi, Dinggang Shen
PAMI
2007
137views more  PAMI 2007»
13 years 4 months ago
Biometrics from Brain Electrical Activity: A Machine Learning Approach
—The potential of brain electrical activity generated as a response to a visual stimulus is examined in the context of the identification of individuals. Specifically, a framewor...
Ramaswamy Palaniappan, Danilo P. Mandic
CVBIA
2005
Springer
13 years 10 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...
ISCAS
2007
IEEE
149views Hardware» more  ISCAS 2007»
13 years 11 months ago
Low-Power Circuits for Brain-Machine Interfaces
—This paper presents work on ultra-low-power circuits for brain–machine interfaces with applications for paralysis prosthetics, stroke, Parkinson’s disease, epilepsy, prosthe...
Rahul Sarpeshkar, Woradorn Wattanapanitch, Benjami...
CVPR
2008
IEEE
14 years 6 months ago
Learning for stereo vision using the structured support vector machine
We present a random field based model for stereo vision with explicit occlusion labeling in a probabilistic framework. The model employs non-parametric cost functions that can be ...
Yunpeng Li, Daniel P. Huttenlocher