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» Learning Mid-Level Features For Recognition
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CIARP
2006
Springer
13 years 11 months ago
Robustness Analysis of the Neural Gas Learning Algorithm
The Neural Gas (NG) is a Vector Quantization technique where a set of prototypes self organize to represent the topology structure of the data. The learning algorithm of the Neural...
Carolina Saavedra, Sebastián Moreno, Rodrig...
ICMLA
2010
13 years 7 months ago
Bayesian Classification of Flight Calls with a Novel Dynamic Time Warping Kernel
Abstract--In this paper we propose a probabilistic classification algorithm with a novel Dynamic Time Warping (DTW) kernel to automatically recognize flight calls of different spec...
Theodoros Damoulas, Samuel Henry, Andrew Farnswort...
JMLR
2012
12 years 3 days ago
Multiresolution Deep Belief Networks
Motivated by the observation that coarse and fine resolutions of an image reveal different structures in the underlying visual phenomenon, we present a model based on the Deep B...
Yichuan Tang, Abdel-rahman Mohamed
AUSAI
2008
Springer
13 years 11 months ago
Learning Object Representations Using Sequential Patterns
This paper explores the use of alternating sequential patterns of local features and saccading actions to learn robust and compact object representations. The temporal encoding rep...
Nobuyuki Morioka
ICIP
2005
IEEE
14 years 11 months ago
Local manifold matching for face recognition
In this paper, we propose a novel classification method, called local manifold matching (LMM), for face recognition. LMM has great representational capacity of available prototypes...
Wei Liu, Wei Fan, Yunhong Wang, Tieniu Tan