ParaLkResNet: an efficient multi-scale image classification network-Reference-Cited by-同舟云学术

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ParaLkResNet: an efficient multi-scale image classification network

Published:2024-06-13 Issue:7 Volume:40 Page:5057-5066
ISSN:0178-2789
Container-title:The Visual Computer
language:en
Short-container-title:Vis Comput

Author:

Yu Tongshuai,Liu Ye,Liu Hao,Chen Ji,Wang Xing

Funder

National Natural Science Foundation of China

Introduction and Cultivation Program for Young Innovative Talents of Universities in Shandong Province

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s00371-024-03508-x.pdf

Reference62 articles.

1. Dai, L., et al.: A deep learning system for detecting diabetic retinopathy across the disease spectrum. Nat. Commun. 12(1), 3242 (2021)

2. Dai, L., et al.: A deep learning system for predicting time to progression of diabetic retinopathy. Nat. Med. 1–11 (2024)

3. Nazir, A., et al.: OFF-eNET: an optimally fused fully end-to-end network for automatic dense volumetric 3D intracranial blood vessels segmentation. IEEE Trans. Image Process. 29, 7192–7202 (2020)

4. Qin, Y., et al.: UrbanEvolver: function-aware urban layout regeneration. Int. J. Comput. Vis. 1–20 (2024)

5. Cheng, Z., et al.: Deep colorization. In: Proceedings of the IEEE International Conference on Computer Vision (2015)

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