Aquabyte, Inc.

Alok Saxena

Cherng Woei Heng

Vooi Leng Tan

Bryton Shang

Computer-implemented techniques for multi-modal aquatic biomass estimation includes determining a fish mass measurement, a fish count, or a direct fish biomass estimate from a sample of one or more digital images or digital video captured by a digital camera immersed underwater in a fish farm enclosure. A technique further includes determining a plurality of fish densities for a plurality of water volumes within the fish farm enclosure based on analysis of signals received from a plurality of bias estimation sensors immersed underwater in the fish farm enclosure. The technique also includes computing a bias-adjusted fish mass measurement, fish count, or direct fish biomass estimate for the fish farm enclosure based on (i) the fish mass measurement, the fish count, or the direct fish biomass estimate determined from the sample of one or more digital images or digital video captured by the digital camera immersed underwater in the fish farm enclosure and (ii) the plurality of fish densities determined for the plurality of water volumes.

Multi-modal aquatic biomass estimation

An optical system for immersion underwater in an aquaculture environment. The optical system captures, in situ, digital images of underwater objects such as freely swimming fish such as, for example, sea salmon or sea trout, as the fish swim naturally in the aquaculture environment. The digital images produced by the optical system are of enough quality such that reliable detection of sea lice in different life stages by a human visual inspection of the digital image or by computer vision systems is enabled.

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San Francisco, CA, United States of America

Alok Saxena