Neural Network Implemented in Numpy and Trained/Evaluated on MNIST
Neural network Numpy Backpropagation Machine learning MNIST
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CoastVision is an open-source Python framework geared towards generating satellite-derived shorelines (SDS) in PlanetScope imagery.
Python Pytorch Unet Machine learning Image segmentation Satellite-derived shorelines GitHub
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Poster presentation 'A Machine Learning Method for Detecting Fog in Mountain Trail Camera Images'
Fog Cloud water interception Image classification Machine learning Computer vision
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Lightning talk at Planet Labs’ 'Rise of the Planetary Variables' event at Planet Headquarters in San Francisco, December 2023
Satellites Earth observation Image segmentation Machine learning Coastal Erosion
Read More29 Jul 2024
Nicolow, J., Sadowski, P., DeLay, J., Juvik, J., T., Tseng, H., & G., Giambelluca (2023). A Machine Learning Method for Detecting Fog in Mountain Trail Camera Images. Hawai‘i Conservation Conference.
Image classification Feature engineering Machine learning Cloud forest Fog
16 Apr 2024
DeLay, J., Nicolow, J., Sadowski, P., G., Giambelluca, T., & Tseng, H. (2024). Determining Fog Frequency with Elevation on Mt. Kaʻala. American Association of Geographes.
Image classification Feature engineering Machine learning Cloud forest Fog
12 Dec 2023
Nicolow, J., Sadowski, P., DeLay, J., Juvik, J., T., Tseng, H., & G., Giambelluca (2023). FogVision: A Machine Learning Method for Detecting Fog in Mountain Trail Camera Images. American Geophysical Union. https://jnicolow.github.io/projects/AGU23.html
Image classification Feature engineering Machine learning Cloud forest Fog
