Applications of deep convolutional neural networks to predict length, circumference, and weight from mostly dewatered images of fish.

Simple biometric data of fish aid fishery management tasks such as monitoring the structure of fish populations and regulating recreational harvest. While these data are foundational to fishery research and management, the collection of length and weight data through physical handling of the fish is challenging as it is time consuming for personnel and can be stressful for the fish. Recent advances in imaging technology and machine learning now offer alternatives for capturing biometric data. To investigate the potential of deep convolutional neural networks to predict biometric data, several regressors were trained and evaluated on data stemming from the FishL™ Recognition System and manual measurements of length, girth, and weight. The dataset consisted of 694 fish from 22 different species common to Laurentian Great Lakes. Even with such a diverse dataset and variety of presentations by the fish, the regressors proved to be robust and achieved competitive mean percent errors in the range of 5.5 to 7.6% for length and girth on an evaluation dataset. Potential applications of this work could increase the efficiency and accuracy of routine survey work by fishery professionals and provide a means for longer-term automated collection of fish biometric data.

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© 2020 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.

Déclaration de conflit d'intérêts

The manuscript describes application of deep learning on images which were captured by a new technology, the FishL™Recognition System, designed and developed by the company at which Janine Byran is employed, Whooshh Innovations, Inc. The use of the system and the subsequently processed images were provided as an in‐kind service by Whooshh to further the scientific inquires of Great Lakes Fishery Commission and Central Michigan University with regard to the future potential of automated prediction of biometric data facilitating fisheries management. Whooshh Innovations, Inc. is a private corporation. All employees hold company stock units and participate in the Employee Stock Option Program. The other authors have no competing interests to declare.