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IJCNN
2000
IEEE
15 years 6 months ago
Classification of Noisy Signals Using Fuzzy ARTMAP Neural Networks
—This paper describes an approach to classification of noisy signals using a technique based on the fuzzy ARTMAP neural network (FAMNN). The proposed method is a modification of ...
Dimitrios Charalampidis, Michael Georgiopoulos, Ta...
ICIP
2007
IEEE
15 years 8 months ago
Steganalyzing Texture Images
A texture image is of noisy nature in its spatial representation. As a result, the data hidden in texture images, in particular in raw texture images, are hard to detect with curr...
Chunhua Chen, Yun Q. Shi, Guorong Xuan
ICMCS
2006
IEEE
182views Multimedia» more  ICMCS 2006»
15 years 8 months ago
Using Semantic Features for Scene Classification: how Good do they Need to Be?
Semantic scene classification is a useful, yet challenging problem in image understanding. Most existing systems are based on low-level features, such as color or texture, and suc...
Matthew R. Boutell, Anustup Choudhury, Jiebo Luo, ...
SSIAI
2000
IEEE
15 years 6 months ago
Content Based Retrieval for Remotely Sensed Imagery
We present a framework for content based retrieval (CBR) of remotely sensed imagery. The main focus of our research is the segmentation step in CBR. A bank of gabor filters is use...
Badrinarayan Raghunathan, Scott T. Acton
ESANN
2006
15 years 3 months ago
Recognition of handwritten digits using sparse codes generated by local feature extraction methods
We investigate when sparse coding of sensory inputs can improve performance in a classification task. For this purpose, we use a standard data set, the MNIST database of handwritte...
Rebecca Steinert, Martin Rehn, Anders Lansner