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» Learning the Relative Importance of Features in Image Data
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DCC
2004
IEEE
16 years 3 months ago
Fast Near-Lossless or Lossless Compression of Large 3D Neuro-Anatomical Images
3D neuro-anatomical images and other volumetric data sets are important in many scientific and biomedical fields. Since such sets may be extremely large, a scalable compression me...
Rongkai Zhao, Michael Gabriel, Geneva G. Belford
PAKDD
2009
ACM
263views Data Mining» more  PAKDD 2009»
15 years 10 months ago
Spatial Weighting for Bag-of-Visual-Words and Its Application in Content-Based Image Retrieval
It is a challenging and important task to retrieve images from a large and highly varied image data set based on their visual contents. Problems like how to fill the semantic gap b...
Xin Chen, Xiaohua Hu, Xiajiong Shen
ICDM
2006
IEEE
164views Data Mining» more  ICDM 2006»
15 years 10 months ago
Unsupervised Learning of Tree Alignment Models for Information Extraction
We propose an algorithm for extracting fields from HTML search results. The output of the algorithm is a database table– a data structure that better lends itself to high-level...
Philip Zigoris, Damian Eads, Yi Zhang
CHI
2008
ACM
16 years 4 months ago
Picbreeder: evolving pictures collaboratively online
Picbreeder is an online service that allows users to collaboratively evolve images. Like in other Interactive Evolutionary Computation (IEC) programs, users evolve images in Picbr...
Jimmy Secretan, Nicholas Beato
148
Voted
AAAI
2012
13 years 6 months ago
Pre-Symptomatic Prediction of Plant Drought Stress Using Dirichlet-Aggregation Regression on Hyperspectral Images
Pre-symptomatic drought stress prediction is of great relevance in precision plant protection, ultimately helping to meet the challenge of “How to feed a hungry world?”. Unfor...
Kristian Kersting, Zhao Xu, Mirwaes Wahabzada, Chr...