Recognition From Web Data: A Progressive Filtering Approach
Leveraging the abundant number of web data is a promising strategy in addressing the problem of data lacking when training convolutional neural networks (CNNs). However, the web images often contain incorrect tags, which may compromise the learned CNN model. To address this problem, this paper focuses on image classification and proposes to iterate between filtering out noisy web labels and fine-tuning the CNN model using the crawled web images. Overall, the proposed method benefits from the...[Show more]
|Collections||ANU Research Publications|
|Source:||IEEE Transactions on Image Processing|
|01_Yang_Recognition_From_Web_Data%3A_A_2018.pdf||5.8 MB||Adobe PDF||Request a copy|
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