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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82 initiative(s)

AI initiative registry
ID	AI Initiative	Current Status	Description	Sector	Region	AI Bucket	SME
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	Quan, Eric
174	AI model for Video review	Idea	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	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	Wang, Yuchen
35	AI-assisted Solution to Detect Ghost Gear from Side Scan Sonar Images	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	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	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	Spearin, Brendan
28	AI-Enabled Electronic Monitoring (EM) Solutions	Pilot	The pilot project, in collabration with Fisheries Resources Management, explores the integration of AI-enabled electronic monitoring (EM) so...	Strategic Policy	National Capital Region	Perception and Understanding	Rémillard, Vincent
165	AIMMS (Artificial Intelligence for Marine Mammals in Survey imagery)	Proof of Concept	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	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	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	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	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	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	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	Winegardner, Amanda
64	Automatic detection of unidentified fish sounds	Pilot	We used Random Forestes and Convolutional Neural Networks (CNN) algorithms trained on manually detected fish sounds to detect fish sounds co...	Ecosystems and Oceans Science	Pacific	Perception and Understanding	Haggarty, Dana
145	Automatic detection of unidentified fish sounds	Pilot	This completed project used Random Forests and Convolutional Neural Networks (CNN) algorithms trained on manually detected fish sounds to de...	Ecosystems and Oceans Science	National Capital Region	Perception and Understanding	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	Winegardner, Amanda
76	Chumputer Vision - salmon scale age predictive AI (See B8)	Idea	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	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	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	Winegardner, Amanda
119	Computer vision to automate fish data extraction from video	Pilot	Our purpose has been to build a tool to broadly apply computer vision methods in marine research. Our work has generated several publication...	Ecosystems and Oceans Science	National Capital Region	Perception and Understanding	Winegardner, Amanda
32	CTD Anomaly Detection	Pilot	The goal of this project is to apply machine learning to detect anomalous oceanographic data, highlighting meaningful physical phenomena in...	Strategic Policy	National Capital Region	Perception and Understanding	Croft, Lee
169	Dark Vessel Detection Platform	Pilot	Utilizes AI and machine learning to detect vessels in satellite imagery, predict movements, and flag potential IUU fishing globally.Automati...	Programs Sector	National Capital Region	Perception and Understanding	Wheeler, Sean
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
62	Deep sea habitat, organism and object detection and identification.	Idea	Proposing a capstone project to Computer Science students from Camosun College to develop a pipeline for identifying objects and loading the...	Ecosystems and Oceans Science	Pacific	Perception and Understanding	Best, Merlin

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
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

Idea Programs Sector Perception and Understanding
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
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

On hold On hold Strategic Policy Perception and Understanding
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
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
28
AI-Enabled Electronic Monitoring (EM) Solutions
The pilot project, in collabration with Fisheries Resources Management, explores the integration of AI-enabled electronic monitoring (EM) solutions to automate the detection and classification of fishing activities using video and sensor data from vessels. This initiative aims to enhance compliance monitoring, reduce manual review time, and support evidence-based fisheries management. Client: Fisheries Resources Management

Pilot Strategic Policy Perception and Understanding
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.

Proof of Concept Fisheries Management Perception and Understanding
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
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
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
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
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
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
64
Automatic detection of unidentified fish sounds
We used Random Forestes and Convolutional Neural Networks (CNN) algorithms trained on manually detected fish sounds to detect fish sounds collected on a passive acoustic monitoring project. The result is an easy-to-use, open-source software called FishSoundFinder, implemented with the CNN detector. Random Forests and CNN

Pilot Ecosystems and Oceans Science Perception and Understanding
145
Automatic detection of unidentified fish sounds
This completed project used Random Forests and Convolutional Neural Networks (CNN) algorithms trained on manually detected fish sounds to detect fish sounds collected on a passive acoustic monitoring project. The result is an easy-to-use, open-source software called FishSoundFinder, implemented with the CNN detector.

Pilot Ecosystems and Oceans Science Perception and Understanding
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
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

Idea Ecosystems and Oceans Science Perception and Understanding
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
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
119
Computer vision to automate fish data extraction from video
Our purpose has been to build a tool to broadly apply computer vision methods in marine research. Our work has generated several publications illustrating how we built, tested/validated, and applied computer vision methodology to collect / extract / and analyze data pertaining to marine fish in the Newfoundland and Labrador region, from video. For example, we have used it to examine the impact of seismic surveying on commercial fish in the Newfoundland and Labrador offshore. Our continuing purpose is now broadly sharing our system with commercial harvesters (fishermen), non-profit organization (AHOI), government researchers (aquaculture, MPAs, AIS), and academics (computing scientists), to collect and rapidly analyzing video data for a wide range of applications.

Pilot Ecosystems and Oceans Science Perception and Understanding
32
CTD Anomaly Detection
The goal of this project is to apply machine learning to detect anomalous oceanographic data, highlighting meaningful physical phenomena in the state of the ocean for closer investigation by scientists. A proof of conept model has been developed to demonstrate feasibility. Further validation is required with the client to verify alignment with the needs of scientists. Client: Pacific Region - Ocean Sciences Division

Pilot Strategic Policy Perception and Understanding
169
Dark Vessel Detection Platform
Utilizes AI and machine learning to detect vessels in satellite imagery, predict movements, and flag potential IUU fishing globally.Automatically cross-references detected vessels with AIS and VMS data to identify unregistered or "dark" vessels. Supports international IUU fishing monitoring; new AI-driven features enable vessel identification from electro-optical imagery. Governance: Managed by DFO’s International Fisheries Enforcement team; technical oversight by MDA Space; coordinated with CSA and other OGDs. Guardrails: All data use complies with commercial licensing terms and GC privacy requirements; sharing restricted

Pilot Programs Sector 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
62
Deep sea habitat, organism and object detection and identification.
Proposing a capstone project to Computer Science students from Camosun College to develop a pipeline for identifying objects and loading the results into Biigle for human review. TBD.

Idea Ecosystems and Oceans Science Perception and Understanding