Classifying tag relevance with relevant positive and negative examples

By Xirong Li, Cees G. M. Snoek. 2013

44 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Yuxin Peng
2. Kuiyuan Yang
3. Yichong Xu
4. Yu Sun
5. Rui Zhang
6. Xiaojie Wang
7. Zheng Zhang
8. Jiaxing Zhang

Citations in the corpus

• The application of two-level attention models in deep convolutional neural network for fine-grained image classification (2014, background): “The goal is to remove noisy patches that are not relevant to the object, which is important to train classifier [13].”
• KDGAN: Knowledge Distillation with Generative Adversarial Networks (2018, methodology): “After convergence, KDGAN consistently outperforms the best baseline REXMP.”