Acknowledgement
Supported by : 한국연구재단
References
- G. E. Hinton and R. R. Salakhutdinov, "Reducing the dimensionality of data with neural networks," Science, pp. 504-507, 2006.
- Alex Krizhevsky, Ilya Sutskever, and Geoffrey E. Hinton, "Imagenet classification with deep convolutional neural networks," Advances in neural information processing systems, 2012.
- Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun, "Faster R-CNN: Towards real-time object detection with region proposal networks," Advances in neural information processing systems, 2015.
- Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian sun, "Deep residual learning for image recognition," Proc. of the IEEE Conference on Computer Vision and Pattern Recognition, 2016.
- Jonathan Long, Evan Shelhamer, and Trevor Darrell, "Fully Convolutional Networks for Semantic Segmentation," Proc. of the IEEE Conference on Computer Vision and Pattern Recognition, 2015.
- Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun, "Spatial pyramid pooling in deep convolutional networks for visual recognition," European Conference on Computer Vision, 2014.
- Ross Girshick, "Fast r-cnn," Proc. of the IEEE International Conference on Computer Vision, 2015.
- Heeyoul Choi, and Yoonhong Min, "Understanding Dropout Algorithms," Journal of KIISE, Vol. 33, No. 8, pp. 32-38, 2015. (in Korean)
- Pierre Baldi and Peter Sadowski, "Understanding dropout," Advances in Neural Information Processing Systems, 2013.
- Nitish Srivastava, Geoffrey Hinton, Al.ex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov, "Dropout: a simple way to prevent neural networks from overfitting," Journal of Machine Learning Research, Vol. 15, No. 1, pp. 1929-1958, 2014.
- Vinod Nair and Geoffrey E. Hinton, "Rectified linear units improve restricted boltzmann machines," Proc. of the 27th International Conference on Machine Learning, 2010.
- Sergey Ioffe, Christrian Szegedy, "Batch normalization: Accelerating deep network training by reducing internal covariate shift," arXiv, 2015.
- Karen Simonyan and Andrew Zisserman, "Very deep convolutional networks for large-scale image recognition," arXiv, 2014.