AI initiative registry

Every initiative listed in the registry can be consulted here, without an account. Each record shows its progress, its milestones and the history of its decisions. Requests still under triage do not appear: they join the registry once reviewed.

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198 current initiative(s)

AI initiative registry
ID	AI Initiative	Stage	Description	Sector	Region	AI Bucket	SME
88	Development of an AI matching model for bowhead whale photo-identification	Pilot	Using DFO’s existing database of bowhead whale photographs, the specific objectives are: 1) Create a machine learning model “detector” for b...	Ecosystems and Oceans Science	National Capital Region	Perception and Understanding	Winegardner, Amanda
89	Augmenting Whale Detection in Satellite Images using synthetic data	Pilot	An autodetector model was built to detect whales in satellite imagery using synthetic imagery. The primary author is now testing the algorit...	Ecosystems and Oceans Science	National Capital Region	Perception and Understanding	Winegardner, Amanda
90	Deep Learning Enhances Beluga Whale Research in the Arctic	Pilot	Esri Canada built a deep learning model that automatically detects beluga whales in imagery. The model was developed using satellite, drone...	Ecosystems and Oceans Science	National Capital Region	Perception and Understanding	Winegardner, Amanda
91	Localization and Tracking of Beluga Whales in Aerial video Using Deep Learning	Pilot	Deep-learning model was developed us YOLOv7 to detect beluga whales from imagery footage. The main contribution of this research is providin...	Ecosystems and Oceans Science	National Capital Region	Perception and Understanding	Winegardner, Amanda
92	Identification automatisée de la condition de carapace de crabe des neiges Not translated · original: French	Pilot	Détermination de la condition de carapace de crabe des neiges à partir d’images. La méthode offre une façon de valider/améliorer des données...	Ecosystems and Oceans Science	National Capital Region	Perception and Understanding	Winegardner, Amanda
93	Détection de homards et de crabes communs dans les images sous-marines par intelligence artificielle. Not translated · original: French	Pilot	Développer un processus de capture et d’analyse d’images sous-marine par Intelligence Artificielle pour la détection de homards et de crabes...	Ecosystems and Oceans Science	National Capital Region	Perception and Understanding	Winegardner, Amanda
94	DFO Bot, deep learning application to analyse otolith images available in DFO Dots	Pilot	Development of a neural network trained using otolith images, expert-derived age estimates, otolith annotations and annuli to obtain age est...	Ecosystems and Oceans Science	National Capital Region	Perception and Understanding	Winegardner, Amanda
95	Optimization of Machine Learning modelling strategy for coastal zooplankton taxonomic identification from flow microscopy imaging.	Pilot	As part of Aquaculture Monitoring Program we are using Ecotaxa's ML algorithm to identify zooplankton. The project aims at identifying the b...	Ecosystems and Oceans Science	National Capital Region	Perception and Understanding	Winegardner, Amanda
96	Use of machine-learning (ML) algorithms and high-performance computing (HPC) for the optimization of satellite image analysis for mapping coastal habitats	Pilot	This project aims to improve satellite image analysis of marine habitats leveraging NRC HPC and ML assets to apply cutting-edge ML technique...	Ecosystems and Oceans Science	National Capital Region	Perception and Understanding	Winegardner, Amanda
97	Satellite image analysis for mapping eelgrass habitat in the southern Gulf of St. Lawrence.	Pilot	This project supports Gulf Region needs for spatial data representing eelgrass habitat through a service level agreement with Marine Plannin...	Ecosystems and Oceans Science	National Capital Region	Perception and Understanding	Winegardner, Amanda
98	Guidance on Optimal Timing for Environmental DNA (GOTeDNA)	Pilot	Provide guidance on optimal eDNA sampling periods and standardized sampling procedures for assessing and monitoring coastal species using eD...	Ecosystems and Oceans Science	National Capital Region	Automation and Decision Support	Winegardner, Amanda
99	Improved freshwater runoff modelling in Eastern Canada to drive ocean models	Pilot	Use Neural Networks to post-process streamflow simulations from the WRF-Hydro model, improving their agreement with observational data. Thes...	Ecosystems and Oceans Science	National Capital Region	Automation and Decision Support	Winegardner, Amanda
100	Development of AI technology for otolith and scale ageing	Pilot	Ageing of scales and otoliths is time-consuming, relies on skilled personnel, and often faces delays. AI tools like DFOdots offer a solution...	Ecosystems and Oceans Science	National Capital Region	Perception and Understanding	Winegardner, Amanda
101	Creating space-time continuous surface chlorophyll fields for northwest Atlantic using neural network methods	Pilot	Neural network methods are applied to fill the space-time gaps in satellite remote sensing data of surface chlorophyll for the Northwest Atl...	Ecosystems and Oceans Science	National Capital Region	Cognitive and Generative AI	Winegardner, Amanda
102	Past, Present and Future Oceanographic Conditions in Canada's MPAs and Marine OECMs (Other Effective area-based Conservation Measures)	Pilot	Downscaling climate models using neural networks for conservation areas. Neural networks allow us to represent coarse resolution climate pro...	Ecosystems and Oceans Science	National Capital Region	Cognitive and Generative AI	Winegardner, Amanda
103	Improved understanding of the processes impacting harmful algal blooms	Pilot	Using machine learning algorithms to analyze phytoplankton images from the Imaging Flow Cytobot (IFCB) to recognize and quantify species ass...	Ecosystems and Oceans Science	National Capital Region	Perception and Understanding	Winegardner, Amanda
104	Zooplankton classification from Video Plankton Recorder	Pilot	Using machine learning algorithms to identify plankton for rapid zooplankton classification from the Video Plankton Recorder, in support of...	Ecosystems and Oceans Science	National Capital Region	Perception and Understanding	Winegardner, Amanda
105	Combining artificial intelligence and drone imagery for automatic extraction of morphometric attributes of small cetaceans: Application to the St. Lawrence Estuary Beluga population.	Pilot	This project proposes to use a multiyear time series of drone images of the St. Lawrence Estuary Beluga population to develop a series of al...	Ecosystems and Oceans Science	National Capital Region	Perception and Understanding	Winegardner, Amanda
106	Finwave: an online photo-identification database and AI matching tool	Pilot	This project aims to improve a publicly accessible machine learning platform capable of identifying individual killer whales in real-time...	Ecosystems and Oceans Science	National Capital Region	Perception and Understanding	Winegardner, Amanda
107	AI tools for translations	Pilot	AI translation tools for all non project-specific communications (e.g., emails, meeting notes, internal taskings). Additional AI tools are n...	Ecosystems and Oceans Science	National Capital Region	Interaction and Engagement	Winegardner, Amanda
108	The development of rapid multiplex qPCR for the detection and quantification of three parasites MSX, SSO, Dermo of oysters (Crassostrea virginica) and MSX single-cell whole genome sequencing using long read sequencing platform’	Pilot	This 2-year project aims to enhance the disease diagnostic services provided to the shellfish aquaculture industry by improving the methods...	Ecosystems and Oceans Science	National Capital Region	Automation and Decision Support	Winegardner, Amanda
109	Advancing Support Systems to Understand the Ocean using AI	Pilot	A workshop will be hosted to identify international best practices and key considerations for using AI technologies to understand and predic...	Ecosystems and Oceans Science	National Capital Region	Infrastructure and Enablement	Winegardner, Amanda
110	Mercator Collaboration on Digital Twins of the Ocean	Pilot	Knowledge exchanges with ECCC and Mercator Océan International on use of AI for ocean modelling, in the context of Digital Twins of the Ocea...	Ecosystems and Oceans Science	National Capital Region	Infrastructure and Enablement	Winegardner, Amanda
111	Digital Twins of the Ocean Task Team	Pilot	National exchanges on topics relating to ocean modelling for development of Digital Twins of the Ocean, including use of AI for modelling an...	Ecosystems and Oceans Science	National Capital Region	Infrastructure and Enablement	Winegardner, Amanda
112	ECCC exchanges on use of AI for ocean modelling	Pilot	Exchanges with ECCC on implementation of machine learning methods for operational ocean forecasting, including potential uses for DFO models...	Ecosystems and Oceans Science	National Capital Region	Infrastructure and Enablement	Winegardner, Amanda

88
Development of an AI matching model for bowhead whale photo-identification
Using DFO’s existing database of bowhead whale photographs, the specific objectives are: 1) Create a machine learning model “detector” for bowhead whales. 2) Create a machine learning individual re-ID model for bowhead whales to re-identify bowheads. 3) To make the detector and matching models accessible through an easy to use, freely available, web-based application, Flukebook.org.

Pilot Ecosystems and Oceans Science Perception and Understanding
89
Augmenting Whale Detection in Satellite Images using synthetic data
An autodetector model was built to detect whales in satellite imagery using synthetic imagery. The primary author is now testing the algorithm on satellite imagery obtained by Arctic Region that has been manually read for whales.

Pilot Ecosystems and Oceans Science Perception and Understanding
90
Deep Learning Enhances Beluga Whale Research in the Arctic
Esri Canada built a deep learning model that automatically detects beluga whales in imagery. The model was developed using satellite, drone and aerial imagery and reported accuracy is high, but the model has not been tested by DFO Science yet.

Pilot Ecosystems and Oceans Science Perception and Understanding
91
Localization and Tracking of Beluga Whales in Aerial video Using Deep Learning
Deep-learning model was developed us YOLOv7 to detect beluga whales from imagery footage. The main contribution of this research is providing a system that accurately detects and tracks features of beluga whales, both adults and calves, from aerial footage.

Pilot Ecosystems and Oceans Science Perception and Understanding
92
Identification automatisée de la condition de carapace de crabe des neiges
Détermination de la condition de carapace de crabe des neiges à partir d’images. La méthode offre une façon de valider/améliorer des données de condition de carapace prises sur le terrain. Ces déterminations sont importantes pour quantifier le recrutement à la pêche durant le relevé scientifique ainsi qu’améliorer la qualité des données de crabe mou dans programme observateur-en-mer.

Pilot Ecosystems and Oceans Science Perception and Understanding
93
Détection de homards et de crabes communs dans les images sous-marines par intelligence artificielle.
Développer un processus de capture et d’analyse d’images sous-marine par Intelligence Artificielle pour la détection de homards et de crabes communs.

Pilot Ecosystems and Oceans Science Perception and Understanding
94
DFO Bot, deep learning application to analyse otolith images available in DFO Dots
Development of a neural network trained using otolith images, expert-derived age estimates, otolith annotations and annuli to obtain age estimates from otoliths.

Pilot Ecosystems and Oceans Science Perception and Understanding
95
Optimization of Machine Learning modelling strategy for coastal zooplankton taxonomic identification from flow microscopy imaging.
As part of Aquaculture Monitoring Program we are using Ecotaxa's ML algorithm to identify zooplankton. The project aims at identifying the best strategy in building model training sets for each region monitored. This strategy will be the basis for future AMP zooplankton identification work.

Pilot Ecosystems and Oceans Science Perception and Understanding
96
Use of machine-learning (ML) algorithms and high-performance computing (HPC) for the optimization of satellite image analysis for mapping coastal habitats
This project aims to improve satellite image analysis of marine habitats leveraging NRC HPC and ML assets to apply cutting-edge ML techniques to the challenges of remote sensing data analysis. Relates to ongoing project (below) through MPC service-level agreement.

Pilot Ecosystems and Oceans Science Perception and Understanding
97
Satellite image analysis for mapping eelgrass habitat in the southern Gulf of St. Lawrence.
This project supports Gulf Region needs for spatial data representing eelgrass habitat through a service level agreement with Marine Planning and Conservation. Machine learning algorithms have been applied for classification of satellite imagery. MPC and Science have been collaborating for several years, annually purchasing satellite imagery, with classification conducted by both groups.

Pilot Ecosystems and Oceans Science Perception and Understanding
98
Guidance on Optimal Timing for Environmental DNA (GOTeDNA)
Provide guidance on optimal eDNA sampling periods and standardized sampling procedures for assessing and monitoring coastal species using eDNA. GOTeDNA, a centralized interactive online tool currently in development, will report/visualize trends in spatio-temporal eDNA distributions.

Pilot Ecosystems and Oceans Science Automation and Decision Support
99
Improved freshwater runoff modelling in Eastern Canada to drive ocean models
Use Neural Networks to post-process streamflow simulations from the WRF-Hydro model, improving their agreement with observational data. These neural networks are applied as a downstream calibration step. Builds synergy between traditional calibration methods and modern AI techniques in hydrologic modeling.

Pilot Ecosystems and Oceans Science Automation and Decision Support
100
Development of AI technology for otolith and scale ageing
Ageing of scales and otoliths is time-consuming, relies on skilled personnel, and often faces delays. AI tools like DFOdots offer a solution by enabling automated ageing using annotated reference collections, helping reduce backlogs and support training. Developing these AI models can enhance resilience, efficiency, and training capacity in ageing programs.

Pilot Ecosystems and Oceans Science Perception and Understanding
101
Creating space-time continuous surface chlorophyll fields for northwest Atlantic using neural network methods
Neural network methods are applied to fill the space-time gaps in satellite remote sensing data of surface chlorophyll for the Northwest Atlantic. The generated dataset will be validated and analyzed.

Pilot Ecosystems and Oceans Science Cognitive and Generative AI
102
Past, Present and Future Oceanographic Conditions in Canada's MPAs and Marine OECMs (Other Effective area-based Conservation Measures)
Downscaling climate models using neural networks for conservation areas. Neural networks allow us to represent coarse resolution climate projections at a much higher spatial resolution across six eastern MPAs.

Pilot Ecosystems and Oceans Science Cognitive and Generative AI
103
Improved understanding of the processes impacting harmful algal blooms
Using machine learning algorithms to analyze phytoplankton images from the Imaging Flow Cytobot (IFCB) to recognize and quantify species associated with harmful algal blooms.

Pilot Ecosystems and Oceans Science Perception and Understanding
104
Zooplankton classification from Video Plankton Recorder
Using machine learning algorithms to identify plankton for rapid zooplankton classification from the Video Plankton Recorder, in support of efforts to assess North Atlantic Right Whale foraging habitat.

Pilot Ecosystems and Oceans Science Perception and Understanding
105
Combining artificial intelligence and drone imagery for automatic extraction of morphometric attributes of small cetaceans: Application to the St. Lawrence Estuary Beluga population.
This project proposes to use a multiyear time series of drone images of the St. Lawrence Estuary Beluga population to develop a series of algorithms for automatic extraction of morphometric information of individual beluga whales using AI.

Pilot Ecosystems and Oceans Science Perception and Understanding
106
Finwave: an online photo-identification database and AI matching tool
This project aims to improve a publicly accessible machine learning platform capable of identifying individual killer whales in real-time from submitted photographs. The ultimate goal is to improve the web-based interface and validate the algorithm used for photo identification against known individuals.

Pilot Ecosystems and Oceans Science Perception and Understanding
107
AI tools for translations
AI translation tools for all non project-specific communications (e.g., emails, meeting notes, internal taskings). Additional AI tools are needed to translate larger projects, as relying on the Translation Bureau is costly and introduces delays in deliverables.

Pilot Ecosystems and Oceans Science Interaction and Engagement
108
The development of rapid multiplex qPCR for the detection and quantification of three parasites MSX, SSO, Dermo of oysters (Crassostrea virginica) and MSX single-cell whole genome sequencing using long read sequencing platform’
This 2-year project aims to enhance the disease diagnostic services provided to the shellfish aquaculture industry by improving the methods for detecting economically important Oyster parasites, enhance understanding of Multinucleate Sphere Unknown X (MSX) virulence dynamics, and support the creation of new vaccine in investigating future outbreaks and modeling through machine learning.

Pilot Ecosystems and Oceans Science Automation and Decision Support
109
Advancing Support Systems to Understand the Ocean using AI
A workshop will be hosted to identify international best practices and key considerations for using AI technologies to understand and predict the ocean.

Pilot Ecosystems and Oceans Science Infrastructure and Enablement
110
Mercator Collaboration on Digital Twins of the Ocean
Knowledge exchanges with ECCC and Mercator Océan International on use of AI for ocean modelling, in the context of Digital Twins of the Ocean.

Pilot Ecosystems and Oceans Science Infrastructure and Enablement
111
Digital Twins of the Ocean Task Team
National exchanges on topics relating to ocean modelling for development of Digital Twins of the Ocean, including use of AI for modelling and products.

Pilot Ecosystems and Oceans Science Infrastructure and Enablement
112
ECCC exchanges on use of AI for ocean modelling
Exchanges with ECCC on implementation of machine learning methods for operational ocean forecasting, including potential uses for DFO models.

Pilot Ecosystems and Oceans Science Infrastructure and Enablement