Advancing 3D point cloud understanding through deep transfer learning: A comprehensive survey-Reference-Cited by-同舟云学术

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Advancing 3D point cloud understanding through deep transfer learning: A comprehensive survey

Published:2025-01 Issue: Volume:113 Page:102601
ISSN:1566-2535
Container-title:Information Fusion
language:en
Short-container-title:Information Fusion

Author:

Sohail Shahab Saquib,Himeur Yassine^ORCID,Kheddar Hamza,Amira Abbes,Fadli Fodil,Atalla Shadi,Copiaco Abigail,Mansoor Wathiq

Publisher

Elsevier BV

Reference350 articles.

1. Video surveillance using deep transfer learning and deep domain adaptation: Towards better generalization;Himeur;Eng. Appl. Artif. Intell.,2023

2. An innovative deep anomaly detection of building energy consumption using energy time-series images;Copiaco;Eng. Appl. Artif. Intell.,2023

3. Attention-enhanced sampling point cloud network (ASPCNet) for efficient 3D tunnel semantic segmentation;Zhou;Autom. Constr.,2023

4. Ai in thyroid cancer diagnosis: Techniques, trends, and future directions;Habchi;Systems,2023

5. Semi-supervised learning-based point cloud network for segmentation of 3D tunnel scenes;Ji;Autom. Constr.,2023

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