Designing Machine Learning into EM Programs: Recent advances and insights from two regions

EM Info Admin

Published July 8, 2019
  • Please register today and join us for this August 1st webinar.

    Commercial fisheries are moving to implement electronic monitoring (EM) for fishery-dependent data collection. Among the substantive barriers for broad-scale implementation, however, are the high costs of video review, transmission, and storage. Currently, EM programs rely on labor-intensive (thus costly) processes, and there is a need to improve the timeliness of data management associated with new EM data streams.

    This webinar will examine advances in incorporating artificial intelligence (AI) and machine learning (ML), provide some lessons-learned, and give insights on how to develop AI-friendly EM programs. Drawing on recent developments and examples from Alaska and New England, it will be of interest to fishermen, fishery managers, scientists, data managers, equipment and service providers, AI/ML engineers, and others. The webinar will also discuss NOAA’s development of open-source machine learning software used for automation, and machine vision camera acquisition software slated for release early in 2020.

    Thursday, Aug 1 2019 2-3pm EST

    Presenters: Brett Alger, Mark Hager and Farron Wallace

    Register now!

    Brett Alger is the NOAA Fisheries’ Electronic Technologies Coordinator, based out of Silver Spring, MD.  He works on technology and policy development, and implementation of electronic monitoring and reporting in fisheries-dependent programs for US fisheries.  Prior to his move to Silver Spring, Brett worked in the NOAA Fisheries Greater Atlantic Regional Fisheries Office in Gloucester, MA, leading efforts to advance electronic monitoring and reporting, and helped coordinate and implement the Northeast Multispecies (groundfish) Fishery Management Plan and groundfish sector program.

    Mark Hager is the Technical Programs Manager at the Gulf of Maine Research Institute. Mark has been working on electronic monitoring and reporting for 6 years and runs operations for a variety of EM efforts in New England. His experience includes vessel installations, software and hardware support, fishermen and vendor training, programmatic design, data analysis, QA/QC, technical systems design, and policy guidance. Mark and his partners are currently working on a variety of AI efforts aimed at creating efficiencies in EM programs.

    Farron Wallace was recently named Director at the Southeast Fisheries Science Center’s Galveston laboratory. Previously, he formed and led the Alaska Electronic Monitoring Innovation project that  developed machine vision stereo and chute camera systems that integrate artificial intelligence to automated image analysis to determine catch size and species identification. These systems are currently deployed to collect discard information in both longline and trawl fisheries in the North Pacific.

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