Multi-scales feature extraction model for water segmentation in satellite image

Author:

Chen Yu-Hsuan1ORCID,Lee Pei-Jun1ORCID,Buil Trong-An1ORCID

Affiliation:

1. National Taiwan University of Science and Technology,Department of Electronic and Computer Engineering,Taipei,Taiwan (R.O.C)

Funder

Ministry of Science and Technology of Taiwan

Publisher

IEEE

Reference9 articles.

1. Towards global flood mapping onboard low cost satellites with machine learning

2. Image Quality Assessment: From Error Visibility to Structural Similarity

3. Reduction deep learning model for floods recognition in satellite images

4. High Frequency Residual Learning for Multi -Scale Image Classification;cheng;BMVC,2019

5. Big-Little Net: An Efficient Multi-Scale Feature Representation for Visual and Speech Recognition;chen;ArXiv,2019

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2. An Enhanced UNet Model to Detect Water Bodies From Remote Sensing Data;2023 International Conference on Information Technology (ICIT);2023-08-09

3. H-BNN: FPGA-based binarized convolutional neural network for cloud detection on satellite payload;2023 International Conference on System Science and Engineering (ICSSE);2023-07-27

4. PanopticRoad: Integrated Panoptic Road Segmentation Under Adversarial Conditions;2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW);2023-06

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