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» Slow Feature Analysis: Unsupervised Learning of Invariances
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ENGL
2007
180views more  ENGL 2007»
14 years 11 months ago
Biological Data Mining for Genomic Clustering Using Unsupervised Neural Learning
— The paper aims at designing a scheme for automatic identification of a species from its genome sequence. A set of 64 three-tuple keywords is first generated using the four type...
Shreyas Sen, Seetharam Narasimhan, Amit Konar
SIGIR
2011
ACM
14 years 2 months ago
Pseudo test collections for learning web search ranking functions
Test collections are the primary drivers of progress in information retrieval. They provide a yardstick for assessing the effectiveness of ranking functions in an automatic, rapi...
Nima Asadi, Donald Metzler, Tamer Elsayed, Jimmy L...
ICMLA
2009
14 years 9 months ago
Exploring Scale-Induced Feature Hierarchies in Natural Images
Recently there has been considerable interest in topic models based on the bag-of-features representation of images. The strong independence assumption inherent in the bag-of-feat...
Jukka Perkiö, Tinne Tuytelaars, Wray L. Bunti...
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ECCV
2010
Springer
15 years 5 months ago
Convolutional learning of spatio-temporal features
Abstract. We address the problem of learning good features for understanding video data. We introduce a model that learns latent representations of image sequences from pairs of su...
ICIP
2006
IEEE
16 years 1 months ago
Unsupervised Image Layout Extraction
We propose a novel unsupervised learning algorithm to extract the layout of an image by learning latent object-related aspects. Unlike traditional image segmentation algorithms th...
David Liu, Datong Chen, Tsuhan Chen