Efficient FPGA Implementation of a Convolutional Neural Network for Surgical Image Segmentation Focusing on Recursive Structure

Author:

Miura Takehiro,Abe Shuto,Manabe Taito,Shibata Yuichiro,Kosaka Taiichiro,Adachi Tomohiko

Publisher

Springer Nature Switzerland

Reference11 articles.

1. Araki, Y., Matsuda, M., Manabe, T., Ishizuka, Y., Shibata: FPGA implementation of convolutional neural networks. In: Proceedings of International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS), pp. 223–233 (2020)

2. Bailey, D.G. (ed.): Image Processing Using FPGAs. MDPI AG (2019)

3. Guo, Q., Yu, Z., Wu, Y., Liang, D., Qin, H., Yan, J.: Dynamic recursive neural network. In: Proceedings of IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 5142–5151 (2019)

4. Gupta, S., Agrawal, A., Gopalakrishnan, K., Narayanan, P.: Deep learning with limited numerical precision. In: Proceedings of International Conference on International Conference on Machine Learning, vol. 37, pp. 1737–1746 (2015)

5. Kim, J., Lee, J.K., Lee, K.M.: Deeply-recursive convolutional network for image super-resolution. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1637–1645 (2016)

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