A. Krizhevsky, I. Sutskever, and G. E. Hinton, “Imagenet classification with deep convolutional neural networks,” in Advances in neural information processing systems, pp. 1097-1105, 2012.
 S. Ren, K. He, R. Girshick, and J. Sun, “Faster R-CNN: Towards realtime object detection with region proposal networks,” in Advances in neural information processing systems, pp. 91-99, 2015.
 R. Girshick, J. Donahue, T. Darrell, and J. Malik, “Rich feature hierarchies for accurate object detection and semantic segmentation,” in Computer Vision and Pattern Recognition, 2014.
 K. He, X. Zhang, S. Ren, and J. Sun, “Spatial pyramid pooling in deep convolutional networks for visual recognition,” in European Conference on Computer Vision, pp. 346-361, Springer, 2014.
 H. Nam, B. Han, Learning Multi-Domain Convolution Neural Networks for Visual Tracking.In CVPR, 2016.
 J. Huang and C. X. Ling, “Using AUC and accuracy in evaluating learning algorithms,” IEEE Transactions on knowledge and Data Engineering, vol. 17, no. 3, pp. 299-310, 2005.
 N. Dalal and B. Triggs, “Histograms of oriented gradients for human detection,” in Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on, vol. 1, pp. 886-893, IEEE, 2005.
 D. G. Lowe, “Distinctive image features from scale-invariant keypoints,” International journal of computer vision, vol. 60, no. 2, pp. 91-110, 2004.
 M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zisserman, “The PASCAL Visual Object Classes Challenge 2012 (VOC2012) Results.” http://www.pascalnetwork.org/challenges/VOC/voc2012/workshop/index.html.
 K. Perlin, “An image synthesizer,” ACM Siggraph Computer Graphics, vol. 19, no. 3, pp. 287-296, 1985. [OpenAIRE]