The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.
Pixel-wise regression using U-Net and its application on pansharpening
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“Models like U-Net [58] and DeepLab [59] can be used for pixel-wise classification, which is useful in highly dense and occluded environments when individuals need to be segmented precisely and distinguish people from backgrounds at a pixel level.”
From A Review of Passenger Counting in Public Transport Concepts with Solution Proposal Based on Image Processing and Machine Learning (2024) · cites this paper as [58]
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Machine Learning in Pansharpening: A benchmark, from shallow to deep networks
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Metadata
- Authors
- Yao, W., Zeng, Z., Lian, C., & Tang, H.
- Affiliations
- South Central Minzu University (CN)
- Huazhong University of Science and Technology (CN)
- Wuhan University of Technology (CN)
- China University of Geosciences (CN)
- Corresponding author
- Zeng, Zhigang
- Venue
- Neurocomputing
- Publisher
- Elsevier BV
- Published
- 2018-10
- Volume
- 312
- Pages
- 364-371
- ISSN
- 0925-2312 (ISSN-L)
- OpenAlex
- W2807567802
- Cited by
- 133
- References
- 38
- Citations by year
- 2026: 7 · 2025: 11 · 2024: 12 · 2023: 20 · 2022: 20 · 2021: 26 · 2020: 21 · 2019: 16
- FWCI
- 11.94
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Neurocomputing (publishedVersion)
- Funders
- Natural Science Foundation of China (61673188, 61503144, 61761130081)
- Natural Science Foundation of Hubei Province (2017CFB519)
- Topics
- Physical Sciences › Engineering › Media Technology › Advanced Image Fusion Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Remote-Sensing Image Classification
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Keywords
- pansharpening, U-Net, convolutional neural networks, remote sensing images, multi-resolution features, geometric deformation, color distortion, image fusion
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