0000000000891129

AUTHOR

Gildardo Lozano-vega

showing 2 related works from this author

Modular Method of Detection, Localization and Counting of Mutliple-Taxon Pollen Apertures Using Bag of Words

2014

International audience; Accurate recognition of airborne pollen taxa is crucial for understanding and treating allergic diseases, which affect an important proportion of the world population. Modern computer vision techniques enables the detection of discriminant characteristics. Apertures is one of these characteristic that has been little explored up to now. In this paper, a flexible method of detection, localization and counting of apertures of different pollen taxa with varying appearances is proposed. Apertures are described based by primitive images following the Bag-of-Words strat-egy. A confidence map is estimated based on the classification of sampled regions. The method is designe…

Contextual image classificationComputer sciencebusiness.industryLocal binary patternspattern recognitionaperturesCognitive neuroscience of visual object recognition[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Image segmentationmedicine.disease_cause[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Atomic and Molecular Physics and OpticsComputer Science Applicationsbag of wordsRobustness (computer science)Bag-of-words modelPollenLBPPattern recognition (psychology)medicineComputer visionArtificial intelligenceElectrical and Electronic Engineeringbusinesspalynology
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Classification of Pollen Apertures Using Bag of Words

2013

International audience; The taxonomical recognition of microscopic biological parti- cles such as pollen and spores is relevant for medical and aerobiological applications. Focusing on an accurate and automatic vision-based pollen recognition system, we propose a method for classification of pollen aper- tures based on bag-of-words strategy, with the ability of learning new types from different taxa without the need of new algorithms. Results demonstrate suitable performance and ability to add new taxa.

Palynology010504 meteorology & atmospheric sciencesbusiness.industryPollen recognitionBiological particles02 engineering and technologyBiologymedicine.disease_cause01 natural sciencesComputingMethodologies_PATTERNRECOGNITIONBag-of-words modelPollen[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]Pattern recognition (psychology)[ INFO.INFO-TI ] Computer Science [cs]/Image Processing0202 electrical engineering electronic engineering information engineeringmedicine020201 artificial intelligence & image processingComputer visionArtificial intelligencebusiness0105 earth and related environmental sciences
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