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» A competitive neural model of small number detection
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GECCO
2010
Springer
191views Optimization» more  GECCO 2010»
13 years 9 months ago
Initialization parameter sweep in ATHENA: optimizing neural networks for detecting gene-gene interactions in the presence of sma
Recent advances in genotyping technology have led to the generation of an enormous quantity of genetic data. Traditional methods of statistical analysis have proved insufficient i...
Emily Rose Holzinger, Carrie C. Buchanan, Scott M....
MM
2005
ACM
172views Multimedia» more  MM 2005»
13 years 10 months ago
Learning the semantics of multimedia queries and concepts from a small number of examples
In this paper we unify two supposedly distinct tasks in multimedia retrieval. One task involves answering queries with a few examples. The other involves learning models for seman...
Apostol Natsev, Milind R. Naphade, Jelena Tesic
NECO
2010
154views more  NECO 2010»
13 years 3 months ago
Role of Homeostasis in Learning Sparse Representations
Neurons in the input layer of primary visual cortex in primates develop edge-like receptive fields. One approach to understanding the emergence of this response is to state that ...
Laurent U. Perrinet
CDC
2008
IEEE
147views Control Systems» more  CDC 2008»
13 years 11 months ago
Clustering neural spike trains with transient responses
— The detection of transient responses, i.e. non– stationarities, that arise in a varying and small fraction of the total number of neural spike trains recorded from chronicall...
John D. Hunter, Jianhong Wu, John G. Milton
ICIP
2005
IEEE
14 years 6 months ago
Trainable post-processing method to reduce false alarms in the detection of small blotches of archive films
We have developed a new semi-automatic neural network based method to detect blotches with low false alarm rate on archive films. Blotches can be modeled as temporal intensity disc...
Attila Licsár, László Cz&uacu...