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GitHub / JoanaR / multi-mode-CNN-pytorch
A PyTorch implementation of the Multi-Mode CNN to reconstruct Chlorophyll-a time series in the global ocean from oceanic and atmospheric physical drivers
JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/JoanaR%2Fmulti-mode-CNN-pytorch
Stars: 6
Forks: 0
Open Issues: 1
License: mit
Language: Jupyter Notebook
Repo Size: 8.97 MB
Dependencies:
0
Created: over 1 year ago
Updated: 6 months ago
Last pushed: about 1 year ago
Last synced: 4 months ago
Commit Stats
Commits: 41
Authors: 1
Mean commits per author: 41.0
Development Distribution Score: 0.0
More commit stats: https://commits.ecosyste.ms/hosts/GitHub/repositories/JoanaR/multi-mode-CNN-pytorch
Topics: attention-mechanisms, biogeochemical-regions, chlorophyll-a, climate, convolutional-neural-networks, deep-learning, earth-observation, global-scale, interpretability, marine-science, ocean-color, oceanography, physical-drivers, phytoplankton, pytorch, regression, remote-sensing, satellite-data, seasonal-interannual-timescale, time-series
Files
No dependencies found