neuralnet

The neural network is a version of MobileNetv2 (224x224 input size) pre-trained on image net and then trained on a subset of images from the 2018 inaturalist dataset. The subset was selected by removing any:

• genus not observed in the US (GBIF query returns at least 1 occurance in US)
• genus not explicitly ignored

All images for species belonging to the same genus were combined resulting in 2988 categories. Some training parameters are:

• 32 image batch size
• 80/20 training/validation split
• 2D global avg pooling and dense layers added on top to adapt model
• Nadam optimizer with sparse_categorical_crossentry loss and sparse_categorical_accuracy
• 0.1 epsilon, 0.001 learning rate
• 20 training epochs

The trained network was then quantized to allow inference on a Google Coral EdgeTPU USB accelerator. Finally, the model is 'served' via a shared memory interface to allow multiple processes to access the USB accelerator.