[7] Ronneberger O, Fischer P, Brox T. U-Net: convolutional networks for biomedical image segmentation[C]//Proceedings of the 2015 18th International Conference on Medical Image Computing and Computer-Assisted Intervention, 2015: 234–241.
[10] Hermans A, Beyer L, Leibe B. In defense of the triplet loss for person re-identification[Z]. arXiv: 1703.07737, 2017. https://doi.org/10.48550/arXiv.1703.07737
[12] Schroff F, Kalenichenko D, Philbin J. FaceNet: a unified embedding for face recognition and clustering[C]//Proceedings of the 2015 IEEE Conference on Computer Vision and Pattern Recognition, 2015: 815–823.
[16] He K M, Zhang X Y, Ren S Q, et al. Deep residual learning for image recognition[C]//Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016: 770–778.
[19] Liu H M, Wang R P, Shan S G, et al. Deep supervised hashing for fast image retrieval[C]//Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016: 2064–2072.
[20] Kim S, Seo M, Laptev I, et al. Deep metric learning beyond binary supervision[C]//Proceedings of the 2017 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2019: 2283–2292.
[21] Arsenault Marc-Olivier. Lossless Triplet loss[EB/OL]. (2018-02-15). http://coffeeanddata.ca/lossless-triplet-loss.
[22] Cheng D, Gong Y H, Zhou S P, et al. Person Re-identification by multi-channel parts-based CNN with improved triplet loss function[C]//Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016: 1335–1344.
[23] Xuan H, Stylianou A, Pless R. Improved embeddings with easy positive triplet mining[C]//Proceedings of the 2020 IEEE Winter Conference on Applications of Computer Vision, 2020: 2463–2471.
[25] Liu W, Wang J, Ji R R, et al. Supervised hashing with kernels[C]//Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012: 2074–2081.
[26] Lin K, Yang H F, Hsiao J H, et al. Deep learning of binary hash codes for fast image retrieval[C]//Proceedings of the 2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2015: 27–35.
[27] Torralba A, Murphy K P, Freeman W T, et al. Context-based vision system for place and object recognition[C]//Proceedings of the Ninth IEEE International Conference on Computer Vision, 2003: 273–280.