Learning to recognition from Bing Clickture data

Chenghua Li, Qiang Song, Yuhang Wang, Hang Song, Qi Kang, Jian Cheng, Hanqing Lu

Abstract: MSR Image Recognition Challenge (IRC) 2016 tries to deal with designing a dog breeds recognition system based on Clickture-Dog dataset. To address the task, we proposed an effective method with systematic strategies as follows. We presented a data cleaning method using faster-rcnn to learn a dog detector. Besides, we ensembeled a series of CNN models to enhance the robustness. A dense evaluation strategy was carried out to boost the test accuracy. Finally, we achieved the first prize of this challenge with 89.65% top-5 accuracy.