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» Modeling Classification and Inference Learning
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CVPR
2007
IEEE
16 years 4 months ago
Learning the Compositional Nature of Visual Objects
The compositional nature of visual objects significantly limits their representation complexity and renders learning of structured object models tractable. Adopting this modeling ...
Björn Ommer, Joachim M. Buhmann
225
Voted
ICCV
2011
IEEE
14 years 2 months ago
Adaptive Deconvolutional Networks for Mid and High Level Feature Learning
We present a hierarchical model that learns image decompositions via alternating layers of convolutional sparse coding and max pooling. When trained on natural images, the layers ...
Matthew D. Zeiler, Graham W. Taylor, Rob Fergus
CVPR
2007
IEEE
16 years 4 months ago
Joint Object Segmentation and Behavior Classification in Image Sequences
In this paper, we propose a general framework for fusing bottom-up segmentation with top-down object behavior classification over an image sequence. This approach is beneficial fo...
Laura Gui, Jean-Philippe Thiran, Nikos Paragios
ICONIP
2008
15 years 3 months ago
A Novel Approach for Hardware Based Sound Classification
Several applications would emerge from the development of efficient and robust sound classification systems able to identify the nature of non-speech sound sources. This paper prop...
Mauricio Kugler, Victor Alberto Parcianello Benso,...
98
Voted
TASLP
2008
98views more  TASLP 2008»
15 years 2 months ago
An Integrative and Discriminative Technique for Spoken Utterance Classification
Abstract-- Traditional methods of spoken utterance classification (SUC) adopt two independently trained phases. In the first phase, an automatic speech recognition (ASR) module ret...
Sibel Yaman, Li Deng, Dong Yu, Ye-Yi Wang, Alex Ac...