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Statements

Subject Item
dbr:Object_categorization
dbo:wikiPageWikiLink
dbr:Object_categorization_from_image_search
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dbr:Object_categorization_from_image_search
Subject Item
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dbr:Object_categorization_from_image_search
Subject Item
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dbr:Object_categorization_from_image_search
Subject Item
dbr:Boosting_(machine_learning)
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Subject Item
dbr:Object_categorization_from_image_search
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Object categorization from image search
rdfs:comment
In computer vision, the problem of object categorization from image search is the problem of training a classifier to recognize categories of objects, using only the images retrieved automatically with an Internet search engine. Ideally, automatic image collection would allow classifiers to be trained with nothing but the category names as input. This problem is closely related to that of content-based image retrieval (CBIR), where the goal is to return better image search results rather than training a classifier for image recognition.
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dbc:Image_search dbc:Object_recognition_and_categorization
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15261743
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1059388664
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dbr:Scale-invariant_feature_transform dbr:Computer_vision dbr:Probabilistic_latent_semantic_analysis dbc:Image_search dbr:Caltech_101 dbr:Kadir–Brady_saliency_detector dbr:Bag_of_words_model dbr:Document_classification dbr:Random_variables dbr:Gaussian_mixture_model dbr:Non-parametric_statistics dbr:Objective_function dbr:Dirichlet_process dbr:Difference_of_Gaussians dbr:Probability_distribution dbr:Expectation_Maximization dbr:Search_engine dbr:PLSA dbr:Expectation_maximization dbc:Object_recognition_and_categorization dbr:Content-based_image_retrieval dbr:Corner_detection dbr:ROC_curve dbr:Statistical_classification dbr:Latent_Dirichlet_allocation dbr:Machine_learning dbr:Gibbs_sampling dbr:Pascal_(programming_language)
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In computer vision, the problem of object categorization from image search is the problem of training a classifier to recognize categories of objects, using only the images retrieved automatically with an Internet search engine. Ideally, automatic image collection would allow classifiers to be trained with nothing but the category names as input. This problem is closely related to that of content-based image retrieval (CBIR), where the goal is to return better image search results rather than training a classifier for image recognition. Traditionally, classifiers are trained using sets of images that are labeled by hand. Collecting such a set of images is often a very time-consuming and laborious process. The use of Internet search engines to automate the process of acquiring large sets of labeled images has been described as a potential way of greatly facilitating computer vision research.
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dbr:Object_categorization_from_image_search