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GitHub / 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.

JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/raoofnaushad%2FLand-Cover-Classification-using-Sentinel-2-Dataset

Stars: 69
Forks: 28
Open issues: 1

License: mit
Language: Jupyter Notebook
Size: 2.12 MB
Dependencies parsed at: Pending

Created at: over 4 years ago
Updated at: 12 months ago
Pushed at: over 1 year ago
Last synced at: 12 months ago

Commit Stats

Commits: 17
Authors: 2
Mean commits per author: 8.5
Development Distribution Score: 0.176
More commit stats: https://commits.ecosyste.ms/hosts/GitHub/repositories/raoofnaushad/Land-Cover-Classification-using-Sentinel-2-Dataset

Topics: data-science, deep-learning, geospatial, geospatial-data, land-cover-classification, land-use-classification, machine-learning, satellite-imagery, sentinel-2, transfer-learning

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