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» Document Retrieval Using SIFT Image Features
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ISBI
2002
IEEE
16 years 11 days ago
Image content-based retrieval and automated interpretation of fluorescence microscope images via the protein subcellular locatio
We describe the Protein Subcellular Location Image Database (PSLID), which collects and structures 2-D through 5-D fluorescence microscope images, annotations, and derived feature...
Kai Huang, Jennifer Lin, James A. Gajnak, Robert F...
ICMCS
2000
IEEE
79views Multimedia» more  ICMCS 2000»
15 years 4 months ago
From Features to Semantics: Some Preliminary Results
In this paper, we present the results of a project that seeks to transform low-level features to a higher level of meaning. This project concerns a technique, latent semantic anal...
Rong Zhao, William I. Grosky
CLUSTER
2009
IEEE
15 years 6 months ago
Accelerating SIFT on parallel architectures
Abstract—SIFT is a widely-used algorithm that extracts features from images; using it to extract information from hundreds of terabytes of aerial and satellite photographs requir...
Seth Warn, Wesley Emeneker, Jackson Cothren, Amy W...
112
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ICCV
2007
IEEE
15 years 6 months ago
Total Recall: Automatic Query Expansion with a Generative Feature Model for Object Retrieval
Given a query image of an object, our objective is to retrieve all instances of that object in a large (1M+) image database. We adopt the bag-of-visual-words architecture which ha...
Ondrej Chum, James Philbin, Josef Sivic, Michael I...
CVPR
2012
IEEE
13 years 2 months ago
On SIFTs and their scales
Scale invariant feature detectors often find stable scales in only a few image pixels. Consequently, methods for feature matching typically choose one of two extreme options: mat...
Tal Hassner, Viki Mayzels, Lihi Zelnik-Manor