Improved Semantic Segmentation for Identification of Flooded Regions in UAV Aerial Images: A Transformer-Based Approach-Reference-Cited by-同舟云学术

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Improved Semantic Segmentation for Identification of Flooded Regions in UAV Aerial Images: A Transformer-Based Approach

Published:2023-07-16 Issue: Volume: Page:
ISSN:
Container-title:IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium
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Author:

Verma Ujjwal¹,Puthumanaillam Gokul²

Affiliation:

1. Manipal Academy of Higher Education,Manipal Institute of Technology Bengaluru,Department of Electronics and Communication Engineering,India

2. University of Illinois Urbana-Champaign,Department of Aerospace Engineering and the Coordinated Science Laboratory,Urbana,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10281394/10281399/10283035.pdf?arnumber=10283035

Reference10 articles.

1. The Cityscapes Dataset for Semantic Urban Scene Understanding

2. Biomedical Image Segmentation: A Survey

3. Segmentation of Tomatoes in Open Field Images with Shape and Temporal Constraints

4. FloodNet: A High Resolution Aerial Imagery Dataset for Post Flood Scene Understanding

5. Comparative Study of Real-Time Semantic Segmentation Networks in Aerial Images During Flooding Events

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