1. Krizhevsky A., Sutskever I., Hinton G. E. ImageNet Classification with Deep Convolutional Neural Networks // Advances in Neural Information Processing Systems / Ed.: F. Pereira, C. J. C. Burges, L. Bottou, K. Q. Weinberger. Curran Associates Inc., 2012. Vol. 25. P. 1097-1105.
2. Deep Residual Learning for Image Recognition / Kaiming He, Xi-Angyu Zhang, Shaoqing Ren, Jian Sun // CoRR. 2015. Vol. ab-s/1512.03385. [Электронный ресурс]: .
3. MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications / A. G. Howard, Menglong Zhu, Bo Chen et al. // CoRR. 2017. Vol. abs/1704.04861. [Электронный ресурс]: .
4. Mask R-CNN / Kaiming He, G. Gkioxari, P. Doll ́ar, R. B. Girshick // CoRR. 2017. Vol. abs/1703.06870. [Электронный ресурс]: .
5. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks / Shaoqing Ren, Kaiming He, R. Girshick, Jian Sun // Advances in Neural Information Processing Systems / Ed.: C. Cortes, N. Lawrence, D. Lee et al. Curran Associates Inc., 2015. Vol. 28. P. 91-99. [Электронный ресурс]: .
6. Kirkpatrick J., Pascanu R., Rabinowitz N. et al. Overcoming catastrophic forgetting in neural networks // Proc. of the National Academy of Sciences. 2017. N 114(13). P. 3521-3526.
7. Zenke F., Poole B., Ganguli S. Continual Learning Through Synaptic Intelligence // Proc. of the 34th Intern. Conf. on Machine Learning. Sydney, Australia. 2017. Vol. 70. P. 3987-3995.
8. Lomonaco V., Maltoni D. CORe50: A New Dataset and Benchmark for Continuous Object Recognition // Proc. of the 1st Annual Conf. on Robot Learning. PMLR. 2017. Vol. 78. P. 17-26.
9. Progressive Neural Networks / A. A.Rusu, N. C. Rabinowitz, G. Desjardins, H. Soyer, J. Kirkpatrick, K. Kavukcuoglu, R. Pascanu, R. Hadsell. // arXiv preprint arXiv:1606.04671, 2016.
10. Hayes T. L., Cahill N. D., Kanan C. Memory Efficient Experience Replay for Streaming Learning // arXiv preprint arXiv:1809.05922, 2018.
11. Rebuffi S. A., Kolesnikov A., Sperl G., Lampert C. H. iCaRL: Incremental Classifier and Representation Learning // IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Honolulu, Hawaii. 2017.
12. Hoffer E., Nir A. Deep metric learning using Triplet network // Intern. Workshop on Similarity-Based Pattern Recognition. Springer, Cham, 2015.
13. Columbia Object Image Library (COIL-100) / S. A. Nene, S. K. Nayar, H. Murase. // Tech. Report CUCS-006-96. 1996. February.
14. Wu Yuxin. Detectron2, 2019. [Электронный ресурс]: .
15. Pytorch: An Imperative Style, High-Performance Deep Learning Library / A. Paszke, S. Gross, F. Massa et al. // Advancesin Neural Information Processing Systems 32 / Ed.: H. Wallach,H. Larochelle, A. Beygelzimer et al. Curran Associates Inc., 2019. P. 8024-8035.
16. Musgrave K., Belongie S., Lim S.-N. Pytorch metric learning // arXiv preprint, arXiv:2008.09164, 2020.