Author:
Majtner Tomáš,Bajić Buda,Herp Jürgen
Publisher
Springer International Publishing
Reference24 articles.
1. Andrearczyk, V., Whelan, P.F.: Deep learning in texture analysis and its application to tissue image classification. In: Biomedical Texture Analysis, pp. 95–129. Elsevier (2017)
2. Bajić, B., Majtner, T., Lindblad, J., Sladoje, N.: Generalised deep learning framework for HEp-2 cell recognition using local binary pattern maps. IET Image Process. 14(6), 1201–1208 (2020)
3. Cheng, J.Z., Chen, C.M., Shen, D.: Deep learning techniques on texture analysis of chest and breast images. In: Biomedical Texture Analysis, pp. 247–279. Elsevier (2017)
4. Faraki, M., Harandi, M.T., Porikli, F.: Approximate infinite-dimensional region covariance descriptors for image classification. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1364–1368. IEEE (2015)
5. Geirhos, R., Rubisch, P., Michaelis, C., Bethge, M., Wichmann, F.A., Brendel, W.: ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness. arXiv preprint arXiv:1811.12231 (2018)
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献