This model is trained to recognize animal species from camera trap pictures.
- Model: AutoML Vision
- Creating datasets: Apache Beam in Dataflow
- Training the model: AutoML in Vertex AI
- Getting predictions: Vertex AI
This model is trained to classify if a ship is fishing or not every hour from their Maritime Mobile Service Identity (MMSI) location data.
- Model: 1D Fully Convolutional Network in Keras
- Creating datasets: Apache Beam in Dataflow
- Training the model: Keras in Vertex AI
- Getting predictions: Keras in Cloud Run
This model uses satellite data to predict if a coal plant is turned on and producing carbon emissions. The satellite data comes from Google Earth Engine.
- Model: 1D Fully Convolutional Network in TensorFlow
- Creating datasets: Sentinel-2 satellite data from Earth Engine
- Training the model: TensorFlow in Vertex AI
- Getting predictions: TensorFlow in Cloud Run
This model uses satellite data to classify what is on Earth. The satellite data comes from Google Earth Engine.
- Model: 2D Fully Convolutional Network in TensorFlow
- Creating datasets: Sentinel-2 satellite data and ESA WorldCover from Earth Engine with Dataflow
- Training the model: TensorFlow in Vertex AI
- Getting predictions: TensorFlow in Cloud Run (real-time) and Dataflow (batch)
This model uses satellite data to forecast precipitation for the next 2 and 6 hours. The satellite data comes from Google Earth Engine.
- Model: 2D Fully Convolutional Network in PyTorch
- Creating datasets: Sentinel-2 satellite data and ESA WorldCover from Earth Engine with Dataflow
- Training the model: PyTorch in Vertex AI
- Getting predictions: PyTorch locally