Dell Technologies has partnered with Australia-based conservation organization Citizens of The Great Barrier Reef in introducing its new deep learning technology model, which will allow global citizen scientists to more quickly and accurately analyze survey images collected from the Great Barrier Reef during the next phase of the Great Reef Census (GRC).
The new Dell deep learning model will better inform conservation efforts for the Great Barrier Reef, one of the world’s greatest natural wonders. A previously implemented Dell edge solution deployed on watercraft automatically uploads data directly to the deep learning model via a mobile network for real-time image capture. This will enhance the capabilities of the GRC by speeding image analysis that previously solely relied on human volunteers – allowing citizen scientists to support prompt recovery efforts in areas that need it the most and during critical times of the year, such as the annual spawning season.
The deep learning analysis now takes less than one minute per photo, compared to seven or eight minutes in previous census phases. While it took 1,516 hours to review 13,000 images in the first GRC, the new model can analyze the same data set in less than 200 hours.
The deep learning semantic segmentation model is powered by a Dell high-performance computing (HPC) graphics processing unit (GPU) accelerated system to train the model and a Dell PowerScale system to store the data. The onshore compute platform includes Dell PowerEdge servers that support an AI training cluster and multiple AI inference engines.