Current Issue

Table of Contents

Volume 16 Number 3 (Fall)

Artificial Intelligence and Machine Learning for Ocean Monitoring and Management
  • Intro
  • Editorial Board
  • On the Cover
  • Publishing Schedule and Advertisements
  • Guest Editor - Dr. Jim Wyse
  • Essays
  • Machine Learning and Marine Science: Critical Role of Partnerships in Norway
  • Nils Olav Handegard, Institute of Marine Research
  • Line Eikvil, Norwegian Computing Center
  • Robert Jenssen, Arctic University of Norway
  • Michael Kampffmeyer, Arctic University of Norway
  • Arnt-Borre Salberg, Norwegian Computing Center
  • Ketil Malde, University of Bergen
  • Drowning in Data: How Artificial Intelligence Could Throw us a Life ring
  • Rylan Command, Fisheries and Marine Institute of Memorial University
  • Katleen Robert, Fisheries and Marine Institute of Memorial University
  • No Machine Learning without Data: Critical Factors to Consider when Collecting Video Data in Marine Environments
  • Malte Pedersen, Aalborg University
  • Niels Madsen, Aalborg University
  • Thomas B. Moeslund, Aalborg University
  • Whale Watching: Automating Aerial and Surface Level Cetacean Monitoring for Improved Population Surveys
  • Michael Outhouse, Deep Vision
  • Alan Parslow, Deep Vision
  • Alvin Beach, Deep Vision
  • The More We Know: Enabling Faster and Smarter Ocean Energy and Mineral Resource Management with Artificial Intelligence
  • J. Jacob Levenson, U.S. Bureau of Ocean Energy Management
  • Timothy White, U.S. Bureau of Ocean Energy Management
  • Jonathan Blythe, U.S. Bureau of Ocean Energy Management
  • Melanie Damour, U.S. Bureau of Ocean Energy Management
  • Christina Bonsell, U.S. Bureau of Ocean Energy Management
  • Catherine Coon, U.S. Bureau of Ocean Energy Management
  • Heather Crowley, U.S. Bureau of Ocean Energy Management
  • Jeleena Almario, U.S. Bureau of Ocean Energy Management
  • Machine Learning Analysis of Underwater Video: Measuring Effects of Seismic Surveying on Groundfish Resources off the Coast of Newfoundland, Canada
  • Corey Morris, Fisheries and Oceans Canada
  • Joshua Barnes, National Research Council Canada
  • Dustin Schornagel, Fisheries and Oceans Canada
  • Christopher Whidden, Dalhousie University
  • Phillippe Lamontagne, National Research Council of Canada
  • The Promise of Artificial Intelligence in Seafood Traceability
  • Aparna Korattywaroopam, ThisFish Inc.
  • Eric Enno Tamm, ThisFish Inc.
  • Reviews & Papers
  • Aquatic Vegetation Mapping using Machine Learning Algorithms and Bathymetric LiDAR Data: A Case Study from Newfoundland and Labrador, Canada
  • Meisam Amani, Wood plc
  • Candace Macdonald, Wood plc
  • Sahel Mahdavi, Wood plc
  • Mardi Gullage, Fisheries and Oceans Canada
  • Justin So, Wood plc
  • Lodestar ... Jasper Kanes, Scott Lowe, Christopher Whidden
  • Technicalities ... Cloud-based Machine Learning Automates Vessel Behaviour Recognition for Maritime Domain Awareness
  • Neil Bomberger, BAE Systems
  • Scott Morales, BAE Systems
  • Karl Severin, BAE Systems
  • Austin Miller, BAE Systems
  • Bradley Rhodes, Crystalytyx
  • Ocean Colour Mapping Using Remote Sensing Technology and an Unsupervised Machine Learning Algorithm
  • Sarah Parsons, Fisheries and Marine Institute of Memorial University
  • Meisam Amani, Wood plc
  • Armin Moghimi, K.N. Toosi University of Tehran
  • Automated Synthetic Aperture Sonar Image Segmentation using Spatially Coherent Clustering
  • Shannon-Morgan Steele, Kraken Robotic Systems Inc.
  • Jillian Ejdrygiewicz, Kraken Robotic Systems Inc.
  • Jeremy Dillon, Kraken Robotic Systems Inc.
  • Identification of Periodic Fish Tags with Deep Learning
  • Santosh Medisetty, Dalhousie University
  • Dave Ouellette, Innovasea
  • Frank Smith, Innovasea
  • Matthew Richard, Innovasea
  • Sam Johnston, Innovasea
  • Jean Quirion, Innovasea
  • Jason Newport, DeepSense
  • Christopher Whidden, Dalhousie University
  • Oliver Kirsebom, MERIDIAN
  • Spindrift
  • Q&A with Blair Thornton
  • Trade Winds
  • Inside Out ... Boulder Detection and Measurement in Side Scan Sonar Data Using Deep Learning
  • Reverberations ... Machine Learning Algorithms to Detect Satellite Navigation Deception: Catching GPS Spoofs with Machine Learning's Neural Networks
  • Jim Wyse, Maridia Research Associates
  • Homeward Bound ... Using Simulation-based Assessments and Machine Learning to Prepare Lifeboat Coxswains for Offshore Emergencies
  • Randy Billard, Virtual Marine
  • Parting Notes ... Greg Harvey