INTERSPEECH
2010
13 years 7 months ago
2010
This paper investigates the combination of discriminative adaptation techniques. The discriminative Maximum A-Posteriori (DMAP) adaptation and discriminative feature Maximum Likel...
TMI
2010
13 years 10 months ago
2010
—A new feature based nonrigid image registration method for magnetic resonance (MR) brain images is presented in this paper. Each image voxel is represented by a rotation invaria...
TASLP
2010
13 years 10 months ago
2010
—A computationally efficient algorithm is proposed for modeling and representing time-varying musical sounds. The aim is to encode individual sounds and not the statistical prop...
TSMC
2002
14 years 2 days ago
2002
We present a method for sampling feature vectors in large (e.g., 2000 5000 16 bit) images that finds subsets of pixel locations which represent "regions" in the image. Sa...
TIP
2002
14 years 2 days ago
2002
In this paper, we introduce a rotational invariant feature set for texture segmentation and classification, based on an extension of fractal dimension (FD) features. The FD extract...
JSS
2002
14 years 3 days ago
2002
This paper details an essential component of a multi-agent distributed knowledge network system for intrusion detection. We describe a distributed intrusion detection architecture...
IJPRAI
2000
14 years 7 days ago
2000
: The main contribution of this report is the development of an integer recurrent artificial neural network (IRANN) for classification of feature vectors. The network consists both...
PAMI
2006
14 years 11 days ago
2006
This paper explores the power and the limitations of weakly supervised categorization. We present a complete framework that starts with the extraction of various local regions of e...
KAIS
2006
14 years 12 days ago
2006
Multi-attribute motion data can be generated in many applications/ devices, such as motion capture devices and animations. It can have dozens of attributes, thousands of rows, and ...
IJCV
2006
14 years 13 days ago
2006
Subspacefacerecognitionoftensuffersfromtwoproblems:(1)thetrainingsamplesetissmallcompared with the high dimensional feature vector; (2) the performance is sensitive to the subspace...