"Dilated cnn"의 두 판 사이의 차이
ph
잔글 |
|||
| 1번째 줄: | 1번째 줄: | ||
| − | ==[https://arxiv.org/pdf/1511.07122.pdf Yu, Fisher, and Vladlen Koltun. "Multi-scale context aggregation by dilated convolutions." arXiv preprint arXiv:1511.07122 (2015).]== | + | == [https://arxiv.org/pdf/1511.07122.pdf Yu, Fisher, and Vladlen Koltun. "Multi-scale context aggregation by dilated convolutions." arXiv preprint arXiv:1511.07122 (2015).] == |
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | ==etc== | + | *dense prediction : "The goal is to compute a discrete or continuous label for each pixel in the image.” |
| − | * CRF : [https://arxiv.org/abs/1412.7062 Chen, Liang-Chieh, et al. "Semantic image segmentation with deep convolutional nets and fully connected crfs." arXiv preprint arXiv:1412.7062 (2014).] | + | **good example is semantic segmentation |
| + | ***multi-scale contextual reasoning? (He et al., 2004; Galleguillos & Belongie, 2010). | ||
| + | **ref. [https://arxiv.org/abs/1611.09288v2 Sercu, Tom, and Vaibhava Goel. "Dense Prediction on Sequences with Time-Dilated Convolutions for Speech Recognition." arXiv preprint arXiv:1611.09288 (2016).] | ||
| + | *'''The familiar discrete convolution is simply the 1-dilated convolution. ''’ | ||
| + | *ref. [http://www.inference.vc/dilated-convolutions-and-kronecker-factorisation/ Dilated Convolutions and Kronecker Factored Convolutions] ★ | ||
| + | **[https://en.wikipedia.org/wiki/Kronecker_product Kronecker product (wikipedia)] | ||
| + | |||
| + | == etc == | ||
| + | |||
| + | *CRF : [https://arxiv.org/abs/1412.7062 Chen, Liang-Chieh, et al. "Semantic image segmentation with deep convolutional nets and fully connected crfs." arXiv preprint arXiv:1412.7062 (2014).] | ||
2017년 3월 24일 (금) 00:45 판
Yu, Fisher, and Vladlen Koltun. "Multi-scale context aggregation by dilated convolutions." arXiv preprint arXiv:1511.07122 (2015).
- dense prediction : "The goal is to compute a discrete or continuous label for each pixel in the image.”
- good example is semantic segmentation
- multi-scale contextual reasoning? (He et al., 2004; Galleguillos & Belongie, 2010).
- ref. Sercu, Tom, and Vaibhava Goel. "Dense Prediction on Sequences with Time-Dilated Convolutions for Speech Recognition." arXiv preprint arXiv:1611.09288 (2016).
- good example is semantic segmentation
- 'The familiar discrete convolution is simply the 1-dilated convolution. ’
- ref. Dilated Convolutions and Kronecker Factored Convolutions ★