Citation notice #10516 · 2026-08-16 06:31:06.326952+00:00
LC-SLab -- An object-based deep learning framework for large-scale land cover classification from satellite imagery and sparse in-situ labels
Correction
Crossref
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cites 10.1016/j.isprsjprs.2019.11.006, which carries a correction notice dated 2020-08-20. One-hop deterministic notice: the citation edge exists in the Pith bibliography graph; no model judged whether the citation was load-bearing.
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01Evidence
Raw extraction · citation context · bibliography index 37
Convolutional Neural Networks and Object-Based Post- Classification Refinement for Land Use and Land Cover Mapping with Optical and SAR Data, Remote Sensing 11 (6) (2019) 690. doi:10.3390/rs11060690. [37] L. Mi, Z. Chen, Superpixel-enhanced deep neural for- est for remote sensing image semantic segmentation, IS- PRS Journal of Photogrammetry and Remote Sensing 159 (2020) 140-152. doi:10.1016/j.isprsjprs.2019.11.006. [38] S. Timilsina, J. Aryal, J. B. Kirkpatrick, Mapping Ur- ban Tree Cover Changes Using Object-Based Convolu- tion Neural Network (OB-CNN), Remote Sensing 12 (18) (2020) 3017. doi:10.3390/rs12183017. [39] D. Ienco, R. Gaetano, R. Interdonato, K. Ose, D. Ho Tong Minh, Combining Sentinel-1 and Sentinel- 2 Time Series via RNN for Object-Based Land Cover
02Event
- Type
- Correction
- Source
- Crossref
- Original DOI
- 10.1016/j.isprsjprs.2019.11.006
- Notice DOI
- 10.1016/j.isprsjprs.2020.08.015
- Date
- 2020-08-20
- Title
- Corrigendum to “Superpixel-enhanced deep neural forest for remote sensing image semantic segmentation” [ISPRS J. Photogramm. Remote Sens. 159 (2020) 140–152]
- Reasons
- ['Erratum']
- Work
- - (2020)
03Dispute this notice
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