Fast Training of Object Detection Using Stochastic Gradient Descent

By Rob G. J. Wijnhoven, P. D. With. 2010

88 citations recorded by the source corpus.

Subfields: Artificial Intelligence, 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 Artificial Intelligence

1. Jianfei Cai
2. Jiuxiang Gu
3. Amir Shahroudy
4. Ahmad Salman
5. Zhenhua Wang
6. Ting Liu
7. Gang Wang
8. Lianyang Ma

In Computer Vision and Pattern Recognition

1. Jianfei Cai
2. G. Wang
3. Jiuxiang Gu
4. Amir Shahroudy
5. Tsuhan Chen
6. Bing Shuai
7. Gang Wang
8. Jason Kuen

Citations in the corpus

• Recent advances in convolutional neural networks (2015, background): “A small η t will lead to a slow convergence, while a large η t will lead to divergence.”
• Learning Speaker-Specific Characteristics With a Deep Neural Architecture (2011, methodology): “After designing an appropriate loss function, the system is trained using Stochastic Gradient Descent (SGD) [121] with the batch training.”