A Novel Curve-Energy Framework to Find the Shortest Possible Lines Through Computer Vision-Reference-Cited by-同舟云学术

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A Novel Curve-Energy Framework to Find the Shortest Possible Lines Through Computer Vision

Published:2022 Issue: Volume: Page:113-119
ISSN:2191-6853
Container-title:Advanced Technologies and Societal Change
language:
Short-container-title:

Author:

Akula Chandra Sekhar,Srinivasulu Asadi,Prathima Ch.

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-19-4044-6_11

Reference12 articles.

1. Yu, H., He, F., Pan, Y.: A novel segmentation model for medical images with intensity inhomogeneity based on adaptive perturbation. Multimedia Tools Appl. 78(9), 11779–11798 (2019)

2. Vyas, S., Chen, T.J., Mohanty, R.R., Jiang, P., Krishnamurthy, V.R.: Latent embedded graphs for image and shape interpolation. Comput. Aided Des. 140, 103091 (2021)

3. Tang, Y., Han, X., Li, Y., Ma, L., Tong, R.: Expressive facial style transfer for personalized memes mimic. Vis. Comput. 35(6), 783–795 (2019)

4. Yu, C., Schumacher, H., Crane, K.: Repulsive curves. ACM Trans. Graph. (TOG) 40(2), 1–21 (2021)

5. Zhang, Y., Chen, H., Islander, S.L., Gong, J., Xiong, G., Yang, T., Liu, K.: Hybrid trajectory planning for autonomous driving in highly constrained environments. IEEE Access 6, 32800–32819 (2018)

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1. A Novel Model for Prediction of Next Word using Machine Learning;2023 7th International Conference on Intelligent Computing and Control Systems (ICICCS);2023-05-17

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