With less than 500 North Atlantic right whales left in the world’s oceans, knowing the health and status of each whale is integral to the efforts of researchers working to protect the species from extinction.
The current process is quite time-consuming and laborious. It starts with photographing right whales during aerial surveys, selecting and importing the photos into a catalog, and finally comparing the photos against known whales in the catalog by trained researchers.
As part of an ongoing preservation effort, NOAA Fisheries launched a Kaggle data science competition to create the best automated process for identifying individual right whales.
Second place finisher Felix Lau describes how he used cuDNN, GeForce GPUs for initial development and an Amazon Web Services GPU instance to train his deep convolutional neural network.
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AI-Generated Summary
- Researchers are working to protect the North Atlantic right whale species, with less than 500 individuals remaining, by monitoring the health and status of each whale.
- The current process of identifying individual whales is time-consuming and laborious, involving photographing whales during aerial surveys and comparing photos against a catalog of known whales.
- Felix Lau, a Kaggle competition finalist, used NVIDIA's cuDNN and GeForce GPUs to develop a deep convolutional neural network that automates the identification process by aligning images to focus on distinctive callosity patterns on the whales.
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