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deepsense.io Wins Kaggle Machine Learning Competition to Automate the Right Whale Recognition Process
MENLO PARK, CA --(Marketwired - January 14, 2016) - deepsense.io's Machine Learning Team has won a major Kaggle competition, developing a machine learning algorithm to automatically identify individual right whales from aerial photographs. After 133 days during which 364 teams submitted 4,788 entries, our team of deep learning experts created the best performing "face recognizer" for right whales, winning by a large margin. The challenge was organized by the National Oceanic and Atmospheric Administration (NOAA), co-sponsored by MathWorks and the data set of 7,000 images (4,500 for training and 2,500 for testing) was provided by the right whale research team from NOAA Fisheries and curated by the New England Aquarium.
"Seeing deep learning techniques help out endangered right whales is uplifting. I hope to see more of such applications in the near future," said Robert Bogucki, Team Captain and CSO at deepsense.io. "We enjoyed the competition immensely."
Our data scientists' winning algorithm used deep learning and convolutional neural networks to localize, align, and finally identify individual right whales from aerial photographs. "Impressive indeed! I am so inspired by this community of data scientists!" said Christin B. Khan, fishery biologist at NOAA. deepsense.io's contribution to automate whale identification could benefit researchers who currently have to go through a painstaking and lengthy process identifying individual whales.
"It was very exciting to have our Machine Learning Team participate and win this NOAA competition because the solution helps solve a real-world problem and empowers fishery biologists in protecting the critically endangered North Atlantic right whales. I'm very proud of this achievement," said Piotr Niedzwiedz, deepsense.io's Co-founder and CTO. "The right whale recognition challenge was a great opportunity to put our data scientists' talents to the test and to demonstrate that deep learning techniques, especially convolutional neural networks can provide immense benefits in big data applications."
For scientists at NOAA Fisheries, the algorithms provide a new standard assisting activities such as: disentangling whales from fishing gear, collecting genetics samples, recording acoustic vocalizations, and assisting with satellite tagging efforts. When the algorithms developed for the Kaggle Right Whale Recognition contest are put to the test and applied in practice successfully, NOAA and other whale researchers could extend the identification technique and use of machine learning to protect other threatened and endangered marine species.
Read more about the competition here: https://www.kaggle.com/c/noaa-right-whale-recognition
For more information on North Atlantic Right Whales, please visit: http://www.nmfs.noaa.gov/pr/species/mammals/whales/north-atlantic-right-whale.html
Kaggle is the leading platform for developing highly sophisticated predictive models and recruiting top data science talent. Through its competitions, Kaggle has built the world's largest community of data scientists, with over 40,000 active participants. They compete with each other to solve complex data science problems, and the top competitors are invited to work on the most interesting and sensitive business problems from some of the world's largest companies.
Ex Google, Facebook and Microsoft software engineers and data scientists, who have built a successful software company in the US and Poland. Currently building a scalable data analytics product called Seahorse -- an agile and comprehensive end-to-end platform built on Apache Spark for Big Data analysis that provides data scientists the capabilities to design, edit and execute Spark applications using a web-based code-free interface. Seahorse's competitive advantage is that it is quick and easy to use, is available on-premises and can process unlimited datasets.
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