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» Learning Mid-Level Features For Recognition
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MLCW
2005
Springer
14 years 1 months ago
Learning Textual Entailment on a Distance Feature Space
Textual Entailment recognition is a very difficult task as it is one of the fundamental problems in any semantic theory of natural language. As in many other NLP tasks, Machine Lea...
Maria Teresa Pazienza, Marco Pennacchiotti, Fabio ...
ICASSP
2011
IEEE
12 years 11 months ago
Deep neural networks for acoustic emotion recognition: Raising the benchmarks
Deep Neural Networks (DNNs) denote multilayer artificial neural networks with more than one hidden layer and millions of free parameters. We propose a Generalized Discriminant An...
André Stuhlsatz, Christine Meyer, Florian E...
ICML
2000
IEEE
14 years 8 months ago
Constructive Feature Learning and the Development of Visual Expertise
We present a framework for learning features for visual discrimination. The learning system is exposed to a sequence of training images. Whenever it fails to recognize a visual co...
Justus H. Piater, Roderic A. Grupen
AR
2011
13 years 2 months ago
Learning, Generation and Recognition of Motions by Reference-Point-Dependent Probabilistic Models
This paper presents a novel method for learning object manipulation such as rotating an object or placing one object on another. In this method, motions are learned using referenc...
Komei Sugiura, Naoto Iwahashi, Hideki Kashioka, Sa...
ICASSP
2011
IEEE
12 years 11 months ago
Multi-view and multi-objective semi-supervised learning for large vocabulary continuous speech recognition
Current hidden Markov acoustic modeling for large vocabulary continuous speech recognition (LVCSR) relies on the availability of abundant labeled transcriptions. Given that speech...
Xiaodong Cui, Jing Huang, Jen-Tzung Chien