AngusG/deep-learning-dreissenid

Source code for reproducing "Predicting Dreissenid Mussel Abundance using Deep Learning" by Galloway et al..

/ 100

Experimental

No commits in the last 6 months.

Stale 6m No Package No Dependents

Maintenance 0 / 25

Adoption 3 / 25

Maturity 9 / 25

Community 0 / 25

Stars

Forks

—

Language

Jupyter Notebook

License

AGPL-3.0

Category

Last pushed

Jun 08, 2023

Commits (30d)

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/AngusG/deep-learning-dreissenid"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.

Higher-rated alternatives

Jordan-Pierce/CoralNet-Toolbox

Tools for panoptic segmentation and developing machine learning models for benthic imagery

NYU-MLDA/OpenABC

OpenABC-D is a large-scale labeled dataset generated by synthesizing open source hardware IPs....

ocean-data-factory-sweden/kso

Notebooks to upload/download marine footage, connect to a citizen science project, train machine...

IQTLabs/AISonobuoy

Maritime Situational Awareness: An Exploration

jackcook/bigger-fish

Code for the paper “There’s Always a Bigger Fish”