Detecting dynamic visual attention in augmented reality aided navigation environment based on a multi-feature integration fully convolutional network-Reference-Cited by-同舟云学术

Detecting dynamic visual attention in augmented reality aided navigation environment based on a multi-feature integration fully convolutional network

Published:2023-01-02 Issue:1 Volume:50 Page:63-78
ISSN:1523-0406
Container-title:Cartography and Geographic Information Science
language:en
Short-container-title:Cartography and Geographic Information Science

Author:

Hei Qiaosong¹^ORCID,Dong Weihua¹^ORCID,Shi Bowen¹^ORCID

Affiliation:

1. State Key Laboratory of Remote Sensing Science, Beijing Key Laboratory for Remote Sensing of Environment and Digital Cities, Research Center of Geospatial Cognition and Visual Analytics, and Faculty of Geographical Science, Beijing Normal University, China

Funder

National Natural Science Foundation of China

State Key Laboratory of Geographic Information Engineering and the Key Laboratory of Surveying and Mapping Science and Geospatial Information Technology of the Ministry of Natural Resources

Publisher

Informa UK Limited

Subject

Management of Technology and Innovation,Geography, Planning and Development,Civil and Structural Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/15230406.2022.2154271

Reference71 articles.

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4. A Database and Evaluation Methodology for Optical Flow

5. Spatio-Temporal Saliency Networks for Dynamic Saliency Prediction

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