Enhancing Security in Cloud Registration with Multi Dimensional Features Fusion-Reference-Cited by-同舟云学术

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Enhancing Security in Cloud Registration with Multi Dimensional Features Fusion

Published:2023-11-23 Issue: Volume: Page:1-7
ISSN:
Container-title:Proceedings of the 5th International Conference on Information Management & Machine Intelligence
language:
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Author:

Mamodiya Udit¹^ORCID,Mutha Rakhi²^ORCID,Reddy Gantla Harish³^ORCID,Pandey Sunil Kr⁴^ORCID,Sayeed Ahmad Sayed⁵^ORCID,Ahuja Vandana⁶^ORCID,Bhattacherjee Abhishek⁷^ORCID

Affiliation:

1. Faculty of Engineering & Technology, Poornima University, India

2. Amity University, India

3. Vignan Institute of Technology and Science, India

4. Institute of Technology & Science, India

5. De Montfort University, United Arab Emirates

6. Swami Vivekanand Institute of Engineering and Technology, India

7. Lovely Professional University, India

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3647444.3652453

Reference20 articles.

1. EFGHNet: A Versatile Image-to-Point Cloud Registration Network for Extreme Outdoor Environment

2. Point Cloud Registration With Object-Centric Alignment

3. P. Zhang "3D Urban Buildings Extraction Based on Airborne LiDAR and Photogrammetric Point Cloud Fusion According to U-Net Deep Learning Model Segmentation " in IEEE Access vol. 10 pp. 20889-20897 doi: 10.1109/ACCESS.2022.3152744 (2022)

4. Efficient Rock-Mass Point Cloud Registration Using $n$ -Point Complete Graphs

5. Automatic Registration Method for TLS LiDAR Data and Image-Based Reconstructed Data

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