On the sampling of web images for learning visual concept classifiers

On the sampling of web images for learning visual concept classifiers

Visual concept learning often requires a large set of training images. In practice, nevertheless, acquiring noise-free training labels with sufficient positive examples is always expensive. A plausible solution for training data collection is by sampling the largely available user-tagged images from...

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Bibliographic Details
Main Authors: ZHU, Shiai, WANG, Gang, NGO, Chong-wah, JIANG, Yu-Gang
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2010
Subjects:
Concept detection
Sampling
Web images
Data Storage Systems
Graphics and Human Computer Interfaces
Online Access:https://ink.library.smu.edu.sg/sis_research/6479
https://ink.library.smu.edu.sg/context/sis_research/article/7482/viewcontent/On_the_sampling_of_web_images_for_learning_visual_concept_classifiers.pdf
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Institution: Singapore Management University
Language: English

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https://ink.library.smu.edu.sg/sis_research/6479
https://ink.library.smu.edu.sg/context/sis_research/article/7482/viewcontent/On_the_sampling_of_web_images_for_learning_visual_concept_classifiers.pdf

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