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Abstract

Detecting whales at sea by visual observation for mitigation purposes is inherently difficult and personal intensive while restricted to daylight hours. These caveats are overcome by the system described herein, which employs a state-of-the-art thermographic infrared scanner in conjunction with a learning computer algorithm to automatically and reliably detect whale blows. The stand-alone system provides detection, verification and documentation of each ship-whale encounter, allowing a retrospective review of every mitigation decision taken aboard. The system has been developed over the course of 5 years and was thoroughly tested in polar waters during 7 expeditions to the Arctic and Antarctic, accumulating 5871 hours of operation. Of these, 3472 hours, were analyzed with various learning automatic detection algorithms, which discovered about 4500 whale blows in this data. Direct comparisons of auto-detections with concurrent whale sightings by visual observers (double blind setup) confirm a very high degree of detection reliability within 2-3 nautical miles from the ship in subpolar and polar environments. The system, when used as a an “assistant”, allows a single marine mammal observer to efficiently monitor the ships entire surroundings and to take instantly and retrospectively verifiable decisions regarding the use of airguns, as all relevant data is automatically stored.

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/content/papers/10.3997/2214-4609.20131189
2013-06-10
2024-04-25
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http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.20131189
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