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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63 current initiative(s)

AI initiative registry
ID	AI Initiative	Stage	Description	Sector	Region	AI Bucket	SME
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 Computer Vision	Winegardner, Amanda
166	Détection de baleines sur les images obtenues par les drones Not translated · original: French	Pilot	Ce projet vise à générer des bases de données d’images annotées et des modèles IA entrainés pour détecter les différentes espèces ou groupes...	Ecosystems and Oceans Science	National Capital Region	Perception and Understanding Computer Vision	Winegardner, Amanda
162	Recherche et développement d’outils de vision automatisée pour l’étude des refuges marins des coraux et des éponges du golfe du Saint-Laurent. Not translated · original: French	Ideation	Projet de contribution avec le Centre de développement et de recherche en intelligence numérique (CDRIN). L’objectif est de concevoir et dév...	Ecosystems and Oceans Science	National Capital Region	Perception and Understanding Computer Vision	Winegardner, Amanda
212	Surveillance électronique en mer Not translated · original: French	Pilot	Il s’agit de capture d’images vidéo sur les navires de pêche pour ensuite les faire analyser par des ressources humaines et un modèle d’inte...	Statistics, Policy and Licensing	Quebec	Perception and Understanding Computer Vision	Rémillard, Vincent
213	Numérisation de documents manuscrits Not translated · original: French	Pilot	En collaboration avec l’équipe nationale de l’Intendant principal des données (PSSI), visant principalement la pêche au saumon. L’objectif e...	Statistics, Policy and Licensing	Quebec	Perception and Understanding Computer Vision	Rémillard, Vincent
218	L’observation des bélugas de l’estuaire du Saint-Laurent Not translated · original: French	Pilot	Entente de contribution avec le Groupe de recherche et d'éducation sur les mammifères marins (GREMM) pour le développement d'un module de me...	Marine Planning and Conservation	Quebec	Perception and Understanding Computer Vision	Robert, Sonia
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 Computer Vision	Winegardner, Amanda
217	Suite du projet de recherche de recherche et développement d’outils de vision automatisée pour l’étude des refuges marins des coraux et des éponges du golfe du Saint-Laurent. Not translated · original: French	Pilot	Une entente de contribution pour l’année 2025-2026 (Programme de gestion des océans) visant à l’amélioration de l’outil développé par le Cen...	Marine Planning and Conservation	Quebec	Perception and Understanding Computer Vision	Brossard, Jade
52	"Chumputer Vision" (see B32) Salmon Scale Aging	Pilot	A model using computer vision to look at images of salmon scale and predict the age of salmon and also monitor its ring growth. CNN and YOL...	Programs Sector	Pacific	Perception and Understanding Computer Vision	Quan, Eric
174	AI model for Video review	Ideation	An AI model that reviews video monitoring footage for a fishery or given vessel and machine learns potential events of non compliance	Programs Sector	National Capital Region	Perception and Understanding Computer Vision	Bédard, Mathieu
34	AI-assisted Marine Mammal Annotation Tool	Pilot	The goal of the project is to improve the efficiency of the aerial image annotation process to reduce manual efforts of the marine mammal sc...	Strategic Policy	National Capital Region	Perception and Understanding Computer Vision	Wang, Yuchen
35	AI-assisted Solution to Detect Ghost Gear from Side Scan Sonar Images	Ideation On hold On hold	The goal of the project is use AI to automate data analysis in detecting Ghost Gear. Client: Ghost Gear Program	Strategic Policy	National Capital Region	Perception and Understanding Computer Vision	Petrovic, Marina
36	AI-assisted Solution to summarize C&P aerial surveillance videos	Pilot	A pilot project to explore the use of AI/ML for automating the identification of relevant segments in EM video and imagery, such as human ac...	Strategic Policy	National Capital Region	Perception and Understanding Computer Vision	Legresley, Jean-Claude
29	AI-Enabled Detection of Watercraft for Aquatic Invasive Species Risk Management	Pilot	This pilot project, in collabration with Aquatic Invasive Species Program, develops an AI-powered system to automatically detect and track...	Strategic Policy	National Capital Region	Perception and Understanding Computer Vision	Spearin, Brendan
165	AIMMS (Artificial Intelligence for Marine Mammals in Survey imagery)	Development	The AIMMS project develops a platform to automate and accelerate the interpretation of aerial imagery for marine mammal population assessmen...	Fisheries Management	National Capital Region	Perception and Understanding Computer Vision	Mosnier, Arnaud
87	ANMPA Habitat Mapping Project	Pilot	Drop camera survey to document seafloor habitats and biological communities in the Anguniaqvia niqiqyuam Marine Protected Area (ANMPA) in th...	Ecosystems and Oceans Science	National Capital Region	Perception and Understanding Computer Vision	Winegardner, Amanda
187	Atlantic Bluefin Tuna Monitoring	Pilot	Automatically perform video analytics from hundred of harvester tuna video Solution being developed in region to assist C&P in batch process...	Indigenous Affairs, Aquaculture and Governance	Gulf	Perception and Understanding Computer Vision	Dupuis, Marc
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 Computer Vision	Winegardner, Amanda
126	Automated assessment of satellite imagery	Pilot	AI routines are being developed and tested to assess large volume of satellite imagery and data to: i) Automatically Identify marine hazards...	Ecosystems and Oceans Science	National Capital Region	Perception and Understanding Computer Vision	Winegardner, Amanda
223	Automated assessment of satellite imagery	Pilot	AI routines are being developed and tested to assess large volume of satellite imagery and data to: i) Automatically Identify marine hazards...	Ecosystems and Oceans Science	Ontario and Prairie	Perception and Understanding Computer Vision	Klein, David
86	Automatic detection of Arctic whales in aerial images	Pilot	In collaboration with Dr. David Clausi and his team at the Vision and Image Processing (VIP) Research Lab (University of Waterloo), we have...	Ecosystems and Oceans Science	National Capital Region	Perception and Understanding Computer Vision	Winegardner, Amanda
159	Chumputer Vision - salmon scale age predictive AI	Pilot	Deep Machine growth pattern Learning of chum salmon scales for predictive age assignments by way of scale pattern interpretation.	Ecosystems and Oceans Science	National Capital Region	Perception and Understanding Computer Vision	Winegardner, Amanda
76	Chumputer Vision - salmon scale age predictive AI (See B8)	Ideation	Deep Machine Learning and Convolutional Neural Network application for the predictive application of age assignment of Chum salmon by way of...	Ecosystems and Oceans Science	Pacific	Perception and Understanding Computer Vision	Wischniowski, Stephen
188	Coastal Surveillance	Pilot	Automatically process thousands of drone images as part of continuous surveillance Solution being developed in region to assist C&P in batch...	Indigenous Affairs, Aquaculture and Governance	Gulf	Perception and Understanding Computer Vision	Dupuis, Marc
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 Computer Vision	Winegardner, Amanda

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 Computer Vision
166
Détection de baleines sur les images obtenues par les drones
Ce projet vise à générer des bases de données d’images annotées et des modèles IA entrainés pour détecter les différentes espèces ou groupes d’espèces visés.

Pilot Ecosystems and Oceans Science Perception and Understanding Computer Vision
162
Recherche et développement d’outils de vision automatisée pour l’étude des refuges marins des coraux et des éponges du golfe du Saint-Laurent.
Projet de contribution avec le Centre de développement et de recherche en intelligence numérique (CDRIN). L’objectif est de concevoir et développer un outil d’intelligence artificielle permettant de détecter et suivre les organismes benthiques filmés dans refuges marins des coraux et des éponges du Golfe du Saint-Laurent.

Ideation Ecosystems and Oceans Science Perception and Understanding Computer Vision
212
Surveillance électronique en mer
Il s’agit de capture d’images vidéo sur les navires de pêche pour ensuite les faire analyser par des ressources humaines et un modèle d’intelligence artificielle doté de capacité d’identification d’événements, d’espèces, etc. Projet fait en collaboration avec l’équipe nationale de l’Intendant principal des données.

Pilot Statistics, Policy and Licensing Perception and Understanding Computer Vision
213
Numérisation de documents manuscrits
En collaboration avec l’équipe nationale de l’Intendant principal des données (PSSI), visant principalement la pêche au saumon. L’objectif est de numériser des documents avec des données manuscrites et de les faire analyser par un modèle d’intelligence artificielle qui va décoder l’écriture pour la transformer en données numériques et les insérer dans une base de données. Le but est de remplacer la saisie manuelle de ces données.

Pilot Statistics, Policy and Licensing Perception and Understanding Computer Vision
218
L’observation des bélugas de l’estuaire du Saint-Laurent
Entente de contribution avec le Groupe de recherche et d'éducation sur les mammifères marins (GREMM) pour le développement d'un module de mesures morphométriques assistées par l’intelligence artificielle pour les bélugas de l'estuaire du Saint-Laurent L’entente s’est terminée le 31 mars 2024 mais le module est en cours d’utilisation. Considérant la contrainte de temps imposée par les mesures manuelles des images prises par drones de bélugas, l’équipe de recherche du GREMM a développé une méthode exploitant l’IA pour mesurer plus rapidement et plus efficacement les bélugas.

Pilot Marine Planning and Conservation Perception and Understanding Computer Vision
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 Computer Vision
217
Suite du projet de recherche de recherche et développement d’outils de vision automatisée pour l’étude des refuges marins des coraux et des éponges du golfe du Saint-Laurent.
Une entente de contribution pour l’année 2025-2026 (Programme de gestion des océans) visant à l’amélioration de l’outil développé par le Centre de développement et de recherche en intelligence numérique (CDRIN) en 2024-2025. Le projet a comme objectif global de concevoir et développer un outil d’intelligence artificielle permettant de détecter et suivre les organismes benthiques filmés dans les refuges marins des coraux et des éponges du Golfe du Saint-Laurent.

Pilot Marine Planning and Conservation Perception and Understanding Computer Vision
52
"Chumputer Vision" (see B32) Salmon Scale Aging
A model using computer vision to look at images of salmon scale and predict the age of salmon and also monitor its ring growth. CNN and YOLO 9. Currently trained on 1478 images.

Pilot Programs Sector Perception and Understanding Computer Vision
174
AI model for Video review
An AI model that reviews video monitoring footage for a fishery or given vessel and machine learns potential events of non compliance

Ideation Programs Sector Perception and Understanding Computer Vision
34
AI-assisted Marine Mammal Annotation Tool
The goal of the project is to improve the efficiency of the aerial image annotation process to reduce manual efforts of the marine mammal science team and reduce time-to-insight for marine mammal survey flights. This project is currently in progress. Business requirements have been finalized and development has commenced Client: Ecosystems and Oceans Science - Ecosystems Science Directorate

Pilot Strategic Policy Perception and Understanding Computer Vision
35
AI-assisted Solution to Detect Ghost Gear from Side Scan Sonar Images
The goal of the project is use AI to automate data analysis in detecting Ghost Gear. Client: Ghost Gear Program

Ideation On hold Strategic Policy Perception and Understanding Computer Vision
36
AI-assisted Solution to summarize C&P aerial surveillance videos
A pilot project to explore the use of AI/ML for automating the identification of relevant segments in EM video and imagery, such as human activity or vessel registration numbers (VRNs). This initiative aims to reduce manual review time and enhance the efficiency of information management in support of fisheries oversight.

Pilot Strategic Policy Perception and Understanding Computer Vision
29
AI-Enabled Detection of Watercraft for Aquatic Invasive Species Risk Management
This pilot project, in collabration with Aquatic Invasive Species Program, develops an AI-powered system to automatically detect and track watercraft at key entry points to prevent the spread of Aquatic Invasive Species (AIS). By enabling early identification of vessels that may carry invasive organisms, the system supports faster inspections and intervention to protect aquatic ecosystems. Initial exploration using sample data is underway, with the project pending ADM approval for installing cameras and data collection. Client: Aquatic Invasive Species Program

Pilot Strategic Policy Perception and Understanding Computer Vision
165
AIMMS (Artificial Intelligence for Marine Mammals in Survey imagery)
The AIMMS project develops a platform to automate and accelerate the interpretation of aerial imagery for marine mammal population assessments. By streamlining annotation and review, and enabling scientists to develop custom machine-learning models without advanced coding skills, the AIMMS workflow significantly reduce processing time, accelerate delivery of science advice, and lower operational costs.

Development Fisheries Management Perception and Understanding Computer Vision
87
ANMPA Habitat Mapping Project
Drop camera survey to document seafloor habitats and biological communities in the Anguniaqvia niqiqyuam Marine Protected Area (ANMPA) in the Inuvialuit Settlement Region. A project sub-objective is to develop AI capacity to detect and record bottom habitat classifications and benthic animals from video still-images, substantially reducing processing times.

Pilot Ecosystems and Oceans Science Perception and Understanding Computer Vision
187
Atlantic Bluefin Tuna Monitoring
Automatically perform video analytics from hundred of harvester tuna video Solution being developed in region to assist C&P in batch processing of at-sea video monitoring footage.

Pilot Indigenous Affairs, Aquaculture and Governance Perception and Understanding Computer Vision
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 Computer Vision
126
Automated assessment of satellite imagery
AI routines are being developed and tested to assess large volume of satellite imagery and data to: i) Automatically Identify marine hazards and ii) Change detection – i.e. shorelines or riverbank changes.

Pilot Ecosystems and Oceans Science Perception and Understanding Computer Vision
223
Automated assessment of satellite imagery
AI routines are being developed and tested to assess large volume of satellite imagery and data to: i) Automatically Identify marine hazards and ii) Change detection – i.e. shorelines or riverbank changes.

Pilot Ecosystems and Oceans Science Perception and Understanding Computer Vision
86
Automatic detection of Arctic whales in aerial images
In collaboration with Dr. David Clausi and his team at the Vision and Image Processing (VIP) Research Lab (University of Waterloo), we have been developing an algorithm to detect narwhals and belugas in photos from aerial surveys. We are planning to expand to ice seals and walrus.

Pilot Ecosystems and Oceans Science Perception and Understanding Computer Vision
159
Chumputer Vision - salmon scale age predictive AI
Deep Machine growth pattern Learning of chum salmon scales for predictive age assignments by way of scale pattern interpretation.

Pilot Ecosystems and Oceans Science Perception and Understanding Computer Vision
76
Chumputer Vision - salmon scale age predictive AI (See B8)
Deep Machine Learning and Convolutional Neural Network application for the predictive application of age assignment of Chum salmon by way of scale images. Chum salmon has been selected as the gateway species due to its relatively easy scale pattern interpretation, this will foster the pathway forward for Chinook, Coho Sockeye and Herring as future targets for AI age interpretation. Deep Machine Learning and Convolutional Neural Network within a Python predictive algorithm

Ideation Ecosystems and Oceans Science Perception and Understanding Computer Vision
188
Coastal Surveillance
Automatically process thousands of drone images as part of continuous surveillance Solution being developed in region to assist C&P in batch processing of drone surveillance images.

Pilot Indigenous Affairs, Aquaculture and Governance Perception and Understanding Computer Vision
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 Computer Vision