raoofnaushad / Land-Cover-Classification-using-Sentinel-2-Dataset

Application of deep learning on Satellite Imagery of Sentinel-2 satellite that move around the earth from June, 2015. This image patches can be trained and classified using transfer learning techniques.

Date Created 2020-11-04 (4 years ago)
Commits 17 (last one about a year ago)
Stargazers 79 (0 this week)
Watchers 2 (0 this week)
Forks 29
License mit
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RepositoryStats indexes 584,777 repositories, of these raoofnaushad/Land-Cover-Classification-using-Sentinel-2-Dataset is ranked #340,649 (42nd percentile) for total stargazers, and #478,954 for total watchers. Github reports the primary language for this repository as Jupyter Notebook, for repositories using this language it is ranked #8,470/17,124.

raoofnaushad/Land-Cover-Classification-using-Sentinel-2-Dataset is also tagged with popular topics, for these it's ranked: deep-learning (#5,621/8398),  machine-learning (#5,330/7935),  data-science (#1,490/2104),  geospatial (#265/378),  transfer-learning (#191/311),  satellite-imagery (#87/143)

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updated: 2024-11-10 @ 08:42pm, id: 310095999 / R_kgDOEnuwfw