## 5 Conclusions
In Proceedings of the 2019 IEEE International Conference on Image Processing (ICIP), Taipei, Taiwan, 22-25 September 2019; IEEE; Piscataway, NJ, USA, 2019; pp. 355-359. * _[PERSON] et al. (2020)_ [PERSON]; [PERSON]; [PERSON]; [PERSON] Cycnn: A rotation invariant cnn using polar mapping and cylindrical convolution layers. _arXiv_**2020**, arXiv:2007.10588. * _[PERSON] et al. (2017)_ [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON] Attention is all you need. _Adv. Neural Inf. Process. Syst._**2017**, _30_, 3058. * _[PERSON] et al. (2020)_ [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON]; et al. An image is worth 16x16 words: Transformers for image recognition at scale. _arXiv_**2020**, arXiv:2010.11929. * _[PERSON] et al. (2021)_ [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Swin transformer: Hierarchical vision transformer using shifted windows. In Proceedings of the IEEE/CVF International Conference on Computer Vision, Montreal, BC, Canada, 10-17 October 2021; pp. 10012-10022. * _[PERSON] et al. (2020)_ [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON] End-to-end object detection with transformers. In Proceedings of the European Conference on Computer Vision, Tel Aviv, Israel, 23-28 October 2020; Springer: Berlin/Heidelberg, Germany, 2020; pp. 213-229. * _[PERSON] and [PERSON] (2014)_ [PERSON]; [PERSON] [PERSON] Deeppose: Human pose estimation via deep neural networks. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Columbus, OH, USA, 23-28 June 2014; pp. 1653-1660. * _[PERSON] et al. (2016)_ [PERSON]; [PERSON]; [PERSON]; [PERSON] Convolutional pose machines. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, NV, USA, 27-30 June 2016; pp. 4724-4732. * _[PERSON] et al. (2020)_ [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Distribution-aware coordinate representation for human pose estimation. In Proceedings of the IEEE/CVF conference on Computer Vision and Pattern Recognition, Seattle, WA, USA, 13-19 June 2020; pp. 7093-7102. * _[PERSON] et al. (2020)_ [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Optic disk and cup segmentation through fuzzy broad learning system for glaucoma screening. _IEEE Trans. Ind. Inform._**2020**, _17_, 2476-2487. [CrossRef]
* _[PERSON] et al. (1992)_ [PERSON]; [PERSON]; [PERSON] The canonical coordinates method for pattern deformation: Theoretical and computational considerations. _IEEE TPAMI_**1992**, _14_, 1171-1183. [CrossRef]
* _[PERSON] et al. (2015)_ [PERSON]; [PERSON]; [PERSON]; [PERSON]. Spatial transformer networks. _Adv. Neural Inf. Process. Syst._**2015**, _28_, 1213. * _[PERSON] et al. (2021)_ [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; et al. Rethinking semantic segmentation from a sequence-to-sequence perspective with transformers. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, Nashville, TN, USA, 20-25 June 2021; pp. 6881-6890. * _[PERSON] et al. (2021)_ [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Transunet: Transformers make strong encoders for medical image segmentation. _arXiv_**2021**, arXiv:2102.04306. * _[PERSON] et al. (2020)_ [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; et al. Refuge challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs. _Med. Image Anal._**2020**, _59_, 101570. [CrossRef]
* _[PERSON] et al. (2014)_ [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON] [PERSON] Drishti-GS: Retinal image dataset for optic nerve head(ONH) segmentation.