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.

Filter 1

Search titles and descriptions

Sector

Program

Stage

Region

Strategic alignment

AI category

Prime Minister's mandate commitment

Declared to TBS

Reset

82 initiative(s)

AI initiative registry
ID	AI Initiative	Current Status	Description	Sector	Region	AI Bucket	SME
151	Zooplankton image analysis	Pilot	Use Random Forest and residual neural networks (ResNet) for automated classification of zooplankton images collected using: 1) scanning of p...	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
23	Video Summarization for Aerial Surveillance	Pilot	AI pilot under development to automatically detect and flag relevant events (e.g., human/vessel activity) in surveillance video for informat...	Programs Sector	National Capital Region	Perception and Understanding	Bédard, Mathieu
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
197	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	Gulf	Perception and Understanding	Dupuis, Marc
118	Use of artificial intelligence models to facilitate seafloor video annotations in conservation areas.	Pilot	The purpose of this initiative is to utilize AI to facilitate seafloor video annotations collected as part of the MCT and Benthic Ecology pr...	Ecosystems and Oceans Science	National Capital Region	Perception and Understanding	Winegardner, Amanda
81	Topaz AI Software	Pilot	Enhance underwater video from ROV and tow camera deployments in the offshore region and elsewhere. The deployment of these platforms is incr...	Ecosystems and Oceans Science	Pacific	Perception and Understanding	Best, Merlin
240	The Current	Proof of Concept	Don't let your harvested data get stuck in still water. Navigate new data streams with AI automation, augmentation and information enablemen...	Fisheries Management	Not region specific	Perception and Understanding	Bird, Tom
212	Surveillance électronique en mer	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	Rémillard, Vincent
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.	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	Brossard, Jade
68	Stereo camera image analysis	Pilot	Tools built in python to automate image analysis and fish measurement tasks. Applications include a conveyor belt camera and underwater towe...	Ecosystems and Oceans Science	Pacific	Perception and Understanding	Rooper, Chris
189	Site Assessments	On hold On hold	Automatically assess presence of eel grass from drone video Solution being developped to assist Fish and Fish Habitat Protection Program in...	Indigenous Affairs, Aquaculture and Governance	Gulf	Perception and Understanding	Dupuis, Marc
228	SILScanner	Pilot	Deploy on DFO's PBMM Cloud a proof of concept application that uses optical character recognition (OCR) to digitize and validate Stream Insp...	Chief Digital Officer	National Capital Region	Perception and Understanding	Bird, Tom
198	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	Gulf	Perception and Understanding	Dupuis, Marc
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
132	Salmon Scale Aging	Pilot	A model using computer vision to look at images of salmon scale and predict the age of salmon and also explain how it arrived at its predict...	Ecosystems and Oceans Science	National Capital Region	Perception and Understanding	Winegardner, Amanda
49	Salmon Fence Counting	Pilot	A model using computer vision to analyze water stream fence video-footage, to simultanously count the number of and predict the species of s...	Programs Sector	Pacific	Perception and Understanding	Quan, Eric
129	Salmon Fence Counting	Pilot	A model using computer vision to analyze water stream fence video-footage, to simultaneously count the number of and predict the species of...	Ecosystems and Oceans Science	National Capital Region	Perception and Understanding	Winegardner, Amanda
50	Salmon Data Digitization (See B22, B26)	Pilot	Digitizing non-machine-readable (handwritten) documents and extracts characters into a digital format so that it is accessible, editable, an...	Programs Sector	Pacific	Perception and Understanding	Quan, Eric
130	Salmon Data Digitization	Pilot	Digitizing non-machine-readable (handwritten) documents and extracts characters into a digital format so that it is accessible, editable, an...	Ecosystems and Oceans Science	National Capital Region	Perception and Understanding	Winegardner, Amanda
161	Remote sensing of the internal tide in the St. Lawrence	Pilot	Using model outputs (STLE500/STLE200) to 1) help identify internal tide surface signature in SWOT (Surface Water and Ocean Topography) data...	Ecosystems and Oceans Science	National Capital Region	Perception and Understanding	Winegardner, Amanda
224	Remote Observation of Watercraft on Roads	Pilot	The Aquatic Invasive Species Program is proposing to launch a pilot initiative aimed at addressing a critical knowledge gap in our understan...	—	Ontario and Prairie	Perception and Understanding	Klein, David
163	Recherches sur l’Intelligence artificielle pour le traitement automatisé des données d’acoustiques sous-marine	Pilot	Nous utilisons les technologies d’apprentissage profond (deep learning) et les détecteurs pour la détection et identification en temps réal...	Ecosystems and Oceans Science	National Capital Region	Perception and Understanding	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.	Idea	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	Winegardner, Amanda
216	Recherche et développement d’outils de vision automatisée pour l’étude des refuges marins des coraux et des éponges du golfe du Saint-Laurent.	Pilot	Une entente de contribution a pour l’année 2024-2025 a été signée avec le Centre de développement et de recherche en intelligence numérique...	Marine Planning and Conservation	Quebec	Perception and Understanding	Brossard, Jade

151
Zooplankton image analysis
Use Random Forest and residual neural networks (ResNet) for automated classification of zooplankton images collected using: 1) scanning of preserved samples (ZooScan); and 2) in situ imagery (Underwater Vision Profiler, UVP). Imagery focused on surveys and samples collected along the West Coast of Vancouver Island and offshore from 2022-present.

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
23
Video Summarization for Aerial Surveillance
AI pilot under development to automatically detect and flag relevant events (e.g., human/vessel activity) in surveillance video for information management. Action plan for this initiative: 1. Governance: Oversight by a multidisciplinary group, routine updates and risk assessments to DM. 2. Guardrails: Pilot with departmental data only, audit outputs for accuracy and bias. 3. Work processes: Deliver targette

Pilot Programs Sector 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
197
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
118
Use of artificial intelligence models to facilitate seafloor video annotations in conservation areas.
The purpose of this initiative is to utilize AI to facilitate seafloor video annotations collected as part of the MCT and Benthic Ecology programs in the NL Region. A large number of vidEcosystems and Oceans Science is collected annually, and manual video annotation (e.g., locating and counting observations) is extremely time-consuming. A published “object detection model” (FathomNet Megalodon Detector, YOLOv8x) trained using marine taxa by MBARI is currently being used to identify objects in our seafloor images. The model does not identify the objects (e.g., to species), but it largely accelerates the process given that locating objects is the most time-consuming part of the work.

Pilot Ecosystems and Oceans Science Perception and Understanding
81
Topaz AI Software
Enhance underwater video from ROV and tow camera deployments in the offshore region and elsewhere. The deployment of these platforms is incredibly time- and resource-consuming, making the optimization of available video an important part of getting the most from this imagery. In addition there are camera limitations from the available DFO survey tools and framegrabs from video will be used as a major product from surveys, making enhancement to high quality images crucial. Topaz Video AI and Topaz Photo AI

Pilot Ecosystems and Oceans Science Perception and Understanding
240
The Current
Don't let your harvested data get stuck in still water. Navigate new data streams with AI automation, augmentation and information enablement. The Current is a cloud-hosted platform that enables users anywhere in the department to ingest large volumes of structured and unstructured documents, extract data using optical character recognition and large language models, validate and review results through human-in-the-loop workflows, and relate extracted information using shared concepts and standards. The architecture emphasizes asynchronous processing, modular extraction services, strong traceability, and governance-ready design. The platform supports configurable extraction tasks, versioned models and definitions, auditable review processes, and future discovery of related research outputs and datasets across heterogeneous sources. As the initial use-case, the Text Intelligence and Data Extraction (TIDE) Service has been developed for the Salmon Habitat Restoration (SHARE) System. TIDE is a baseline iteration of The Current that fulfills the minimum viable product requirements of SHARE. TIDE focuses on digitizing, extracting, and modeling data from large unstructured text documents. TIDE establishes the baseline architecture and demonstrates a scalable workflow in Production.

Proof of Concept Fisheries Management Perception and Understanding
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
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
68
Stereo camera image analysis
Tools built in python to automate image analysis and fish measurement tasks. Applications include a conveyor belt camera and underwater towed stereo camera system Computer vision tools (Python, Viame)

Pilot Ecosystems and Oceans Science Perception and Understanding
189
Site Assessments
Automatically assess presence of eel grass from drone video Solution being developped to assist Fish and Fish Habitat Protection Program in reviewing hundreds of hours of drone footage to detect presence of Eel Grass.

On hold On hold Indigenous Affairs, Aquaculture and Governance Perception and Understanding
228
SILScanner
Deploy on DFO's PBMM Cloud a proof of concept application that uses optical character recognition (OCR) to digitize and validate Stream Inspection Logs (SILs). The PoC was originally developed on SSC's cloud infrastructure. It is now being deployed in DFO PB cloud infrastructure. BLADES initiative and IT security teams are involved.

Pilot Chief Digital Officer Perception and Understanding
198
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
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
132
Salmon Scale Aging
A model using computer vision to look at images of salmon scale and predict the age of salmon and also explain how it arrived at its prediction.

Pilot Ecosystems and Oceans Science Perception and Understanding
49
Salmon Fence Counting
A model using computer vision to analyze water stream fence video-footage, to simultanously count the number of and predict the species of salmon. YOLO 11 Chinook trained on 735 annotated frames from 63 videos Coho trained on 432 annotated frames from 44 videos Sockeye trained on 1149 annotated frames from 36 videos Chum untrained (annotation of 1368 frames from 43 videos in progress) Pink Humpback

Pilot Programs Sector Perception and Understanding
129
Salmon Fence Counting
A model using computer vision to analyze water stream fence video-footage, to simultaneously count the number of and predict the species of salmon.

Pilot Ecosystems and Oceans Science Perception and Understanding
50
Salmon Data Digitization (See B22, B26)
Digitizing non-machine-readable (handwritten) documents and extracts characters into a digital format so that it is accessible, editable, and useable for analysis. Document Intelligence - Custom Classification and Extraction Model Azure OpenAI GPT4o mini Data and Information from ~45,000 pages have been digitized

Pilot Programs Sector Perception and Understanding
130
Salmon Data Digitization
Digitizing non-machine-readable (handwritten) documents and extracts characters into a digital format so that it is accessible, editable, and useable for analysis.

Pilot Ecosystems and Oceans Science Perception and Understanding
161
Remote sensing of the internal tide in the St. Lawrence
Using model outputs (STLE500/STLE200) to 1) help identify internal tide surface signature in SWOT (Surface Water and Ocean Topography) data and 2) train an AI to detect internal tide in SWOT data.

Pilot Ecosystems and Oceans Science Perception and Understanding
224
Remote Observation of Watercraft on Roads
The Aquatic Invasive Species Program is proposing to launch a pilot initiative aimed at addressing a critical knowledge gap in our understanding the spread of aquatic invasive species. Invasive species can attach to boats, trailers, and related equipment—a process commonly referred to as the "stowaway pathway"—which enables their unintentional spread across ecosystems when watercraft are transported between water bodies. The AIS Program is seeking to understand watercraft movement into Canada via international land border crossings. Currently, the extent of this "stowaway" pathway remains largely unquantified. To address this, the pilot will deploy remote camera systems at select border entry points to capture imagery of incoming vehicles. Leveraging machine learning, the system will automatically identify and flag images containing watercraft. This data-driven approach will provide actionable insights to inform strategic decisions on the timing and placement of watercraft inspection and decontamination resources. This initiative may represent a significant step toward enhancing our ability to proactively manage aquatic invasive species risks at key entry points.

Pilot Perception and Understanding
163
Recherches sur l’Intelligence artificielle pour le traitement automatisé des données d’acoustiques sous-marine
Nous utilisons les technologies d’apprentissage profond (deep learning) et les détecteurs pour la détection et identification en temps réal des espèces de mammifères marins telles que la baleine noire de l’Atlantique.

Pilot Ecosystems and Oceans Science Perception and Understanding
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.

Idea Ecosystems and Oceans Science Perception and Understanding
216
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 a pour l’année 2024-2025 a été signée avec le Centre de développement et de recherche en intelligence numérique (CDRIN) pour 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. L’entente s’est terminée le 31 mars 2025.

Pilot Marine Planning and Conservation Perception and Understanding