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» Learning Mid-Level Features For Recognition
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IJCNN
2007
IEEE
14 years 1 months ago
Default ARTMAP 2
—Default ARTMAP combines winner-take-all category node activation during training, distributed activation during testing, and a set of default parameter values that define a read...
Gregory P. Amis, Gail A. Carpenter
SIGIR
2005
ACM
14 years 1 months ago
On the collective classification of email "speech acts"
We consider classification of email messages as to whether or not they contain certain “email acts”, such as a request or a commitment. We show that exploiting the sequential ...
Vitor Rocha de Carvalho, William W. Cohen
ICASSP
2010
IEEE
13 years 7 months ago
Semi-Supervised Fisher Linear Discriminant (SFLD)
Supervised learning uses a training set of labeled examples to compute a classifier which is a mapping from feature vectors to class labels. The success of a learning algorithm i...
Seda Remus, Carlo Tomasi
CVPR
2009
IEEE
15 years 2 months ago
A Multi-View Probabilistic Model for 3D Object Classes
We propose a novel probabilistic framework for learning visual models of 3D object categories by combining appearance information and geometric constraints. Objects are represen...
Fei-Fei Li 0002, Hao Su, Min Sun, Silvio Savarese
MIR
2006
ACM
141views Multimedia» more  MIR 2006»
14 years 1 months ago
Mining temporal patterns of movement for video content classification
Scalable approaches to video content classification are limited by an inability to automatically generate representations of events ode abstract temporal structure. This paper pre...
Michael Fleischman, Philip DeCamp, Deb Roy