Registre des initiatives en IA

Toutes les initiatives inscrites au registre sont consultables ici, sans compte. Chaque fiche montre son avancement, ses jalons et l'historique de ses décisions. Les demandes encore en cours de triage n'y figurent pas : elles rejoignent le registre une fois examinées.

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63 initiative(s) courante(s)

Registre des initiatives en IA
ID	Initiative en IA	Étape	Description	Secteur	Région	Catégorie d'IA	Expert en la matière
89	Augmenting Whale Detection in Satellite Images using synthetic data Non traduit · origine : anglais	Pilote	An autodetector model was built to detect whales in satellite imagery using synthetic imagery. The primary author is now testing the algorit...	Sciences des écosystèmes et des océans	Région de la capitale nationale	Perception et compréhension Vision par ordinateur	Winegardner, Amanda
74	Pacific Plankton Monitoring: Imagery and automated classification Non traduit · origine : anglais	Pilote	• Monitoring of zooplankton and phytoplankton in the water column with shipboard and benchtop plankton imaging instruments (UVP, ZooScan, Pl...	Sciences des écosystèmes et des océans	Pacifique	Perception et compréhension Vision par ordinateur	Sastri, Akash
49	Salmon Fence Counting Non traduit · origine : anglais	Pilote	A model using computer vision to analyze water stream fence video-footage, to simultanously count the number of and predict the species of s...	Secteur des programmes	Pacifique	Perception et compréhension Vision par ordinateur	Quan, Eric
36	AI-assisted Solution to summarize C&P aerial surveillance videos Non traduit · origine : anglais	Pilote	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...	Politiques stratégiques	Région de la capitale nationale	Perception et compréhension Vision par ordinateur	Legresley, Jean-Claude
35	AI-assisted Solution to Detect Ghost Gear from Side Scan Sonar Images Non traduit · origine : anglais	Idéation En pause En pause	The goal of the project is use AI to automate data analysis in detecting Ghost Gear. Client: Ghost Gear Program	Politiques stratégiques	Région de la capitale nationale	Perception et compréhension Vision par ordinateur	Petrovic, Marina
34	AI-assisted Marine Mammal Annotation Tool Non traduit · origine : anglais	Pilote	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...	Politiques stratégiques	Région de la capitale nationale	Perception et compréhension Vision par ordinateur	Wang, Yuchen
33	Machine-learning-assisted Benthic Marine Life Annotation Tool Non traduit · origine : anglais	Idéation En pause En pause	The goal of the project is to improve the efficiency of the image annotation process to reduce manual efforts of the benthic science team an...	Politiques stratégiques	Région de la capitale nationale	Perception et compréhension Vision par ordinateur	Wang, Yuchen
29	AI-Enabled Detection of Watercraft for Aquatic Invasive Species Risk Management Non traduit · origine : anglais	Pilote	This pilot project, in collabration with Aquatic Invasive Species Program, develops an AI-powered system to automatically detect and track...	Politiques stratégiques	Région de la capitale nationale	Perception et compréhension Vision par ordinateur	Spearin, Brendan
23	Video Summarization for Aerial Surveillance Non traduit · origine : anglais	Pilote	AI pilot under development to automatically detect and flag relevant events (e.g., human/vessel activity) in surveillance video for informat...	Secteur des programmes	Région de la capitale nationale	Perception et compréhension Vision par ordinateur	Bédard, Mathieu
52	"Chumputer Vision" (see B32) Salmon Scale Aging Non traduit · origine : anglais	Pilote	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...	Secteur des programmes	Pacifique	Perception et compréhension Vision par ordinateur	Quan, Eric
86	Automatic detection of Arctic whales in aerial images Non traduit · origine : anglais	Pilote	In collaboration with Dr. David Clausi and his team at the Vision and Image Processing (VIP) Research Lab (University of Waterloo), we have...	Sciences des écosystèmes et des océans	Région de la capitale nationale	Perception et compréhension Vision par ordinateur	Winegardner, Amanda
87	ANMPA Habitat Mapping Project Non traduit · origine : anglais	Pilote	Drop camera survey to document seafloor habitats and biological communities in the Anguniaqvia niqiqyuam Marine Protected Area (ANMPA) in th...	Sciences des écosystèmes et des océans	Région de la capitale nationale	Perception et compréhension Vision par ordinateur	Winegardner, Amanda
88	Development of an AI matching model for bowhead whale photo-identification Non traduit · origine : anglais	Pilote	Using DFO’s existing database of bowhead whale photographs, the specific objectives are: 1) Create a machine learning model “detector” for b...	Sciences des écosystèmes et des océans	Région de la capitale nationale	Perception et compréhension Vision par ordinateur	Winegardner, Amanda
81	Topaz AI Software Non traduit · origine : anglais	Pilote	Enhance underwater video from ROV and tow camera deployments in the offshore region and elsewhere. The deployment of these platforms is incr...	Sciences des écosystèmes et des océans	Pacifique	Perception et compréhension Vision par ordinateur	Best, Merlin
90	Deep Learning Enhances Beluga Whale Research in the Arctic Non traduit · origine : anglais	Pilote	Esri Canada built a deep learning model that automatically detects beluga whales in imagery. The model was developed using satellite, drone...	Sciences des écosystèmes et des océans	Région de la capitale nationale	Perception et compréhension Vision par ordinateur	Winegardner, Amanda
91	Localization and Tracking of Beluga Whales in Aerial video Using Deep Learning Non traduit · origine : anglais	Pilote	Deep-learning model was developed us YOLOv7 to detect beluga whales from imagery footage. The main contribution of this research is providin...	Sciences des écosystèmes et des océans	Région de la capitale nationale	Perception et compréhension Vision par ordinateur	Winegardner, Amanda
94	DFO Bot, deep learning application to analyse otolith images available in DFO Dots Non traduit · origine : anglais	Pilote	Development of a neural network trained using otolith images, expert-derived age estimates, otolith annotations and annuli to obtain age est...	Sciences des écosystèmes et des océans	Région de la capitale nationale	Perception et compréhension Vision par ordinateur	Winegardner, Amanda
95	Optimization of Machine Learning modelling strategy for coastal zooplankton taxonomic identification from flow microscopy imaging. Non traduit · origine : anglais	Pilote	As part of Aquaculture Monitoring Program we are using Ecotaxa's ML algorithm to identify zooplankton. The project aims at identifying the b...	Sciences des écosystèmes et des océans	Région de la capitale nationale	Perception et compréhension Vision par ordinateur	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 Non traduit · origine : anglais	Pilote	This project aims to improve satellite image analysis of marine habitats leveraging NRC HPC and ML assets to apply cutting-edge ML technique...	Sciences des écosystèmes et des océans	Région de la capitale nationale	Perception et compréhension Vision par ordinateur	Winegardner, Amanda
97	Satellite image analysis for mapping eelgrass habitat in the southern Gulf of St. Lawrence. Non traduit · origine : anglais	Pilote	This project supports Gulf Region needs for spatial data representing eelgrass habitat through a service level agreement with Marine Plannin...	Sciences des écosystèmes et des océans	Région de la capitale nationale	Perception et compréhension Vision par ordinateur	Winegardner, Amanda
100	Development of AI technology for otolith and scale ageing Non traduit · origine : anglais	Pilote	Ageing of scales and otoliths is time-consuming, relies on skilled personnel, and often faces delays. AI tools like DFOdots offer a solution...	Sciences des écosystèmes et des océans	Région de la capitale nationale	Perception et compréhension Vision par ordinateur	Winegardner, Amanda
103	Improved understanding of the processes impacting harmful algal blooms Non traduit · origine : anglais	Pilote	Using machine learning algorithms to analyze phytoplankton images from the Imaging Flow Cytobot (IFCB) to recognize and quantify species ass...	Sciences des écosystèmes et des océans	Région de la capitale nationale	Perception et compréhension Vision par ordinateur	Winegardner, Amanda
104	Zooplankton classification from Video Plankton Recorder Non traduit · origine : anglais	Pilote	Using machine learning algorithms to identify plankton for rapid zooplankton classification from the Video Plankton Recorder, in support of...	Sciences des écosystèmes et des océans	Région de la capitale nationale	Perception et compréhension Vision par ordinateur	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. Non traduit · origine : anglais	Pilote	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...	Sciences des écosystèmes et des océans	Région de la capitale nationale	Perception et compréhension Vision par ordinateur	Winegardner, Amanda
228	SILScanner Non traduit · origine : anglais	Pilote	Deploy on DFO's PBMM Cloud a proof of concept application that uses optical character recognition (OCR) to digitize and validate Stream Insp...	Dirigeant principal du numérique	Région de la capitale nationale	Perception et compréhension Vision par ordinateur	Bird, Tom

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.

Pilote Sciences des écosystèmes et des océans Perception et compréhension Vision par ordinateur
74
Pacific Plankton Monitoring: Imagery and automated classification
• Monitoring of zooplankton and phytoplankton in the water column with shipboard and benchtop plankton imaging instruments (UVP, ZooScan, PlanktoScope). • Application of automated classification of survey and preserved sample image data sets to complement and enhance spatial and temporal resolution of monitoring in Canada’s EEZ and offshore NE Pacific. Development of and regular optimization of automated image classification models using AI: deep learning (residual networks) and machine learning (random forests) methods.

Pilote Sciences des écosystèmes et des océans Perception et compréhension Vision par ordinateur
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

Pilote Secteur des programmes Perception et compréhension Vision par ordinateur
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.

Pilote Politiques stratégiques Perception et compréhension Vision par ordinateur
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

Idéation En pause Politiques stratégiques Perception et compréhension Vision par ordinateur
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

Pilote Politiques stratégiques Perception et compréhension Vision par ordinateur
33
Machine-learning-assisted Benthic Marine Life Annotation Tool
The goal of the project is to improve the efficiency of the image annotation process to reduce manual efforts of the benthic science team and reduce time-to-insight from underwater surveys. Further development is prevented by DFO's IT infrastructure. There are ongoing discussions with CDOS to resolved this but the project is on hold in the meantime. Client: Quebec Region/Pacific Region - Oceans and Ecosystem Sciences Division

Idéation En pause Politiques stratégiques Perception et compréhension Vision par ordinateur
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

Pilote Politiques stratégiques Perception et compréhension Vision par ordinateur
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

Pilote Secteur des programmes Perception et compréhension Vision par ordinateur
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.

Pilote Secteur des programmes Perception et compréhension Vision par ordinateur
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.

Pilote Sciences des écosystèmes et des océans Perception et compréhension Vision par ordinateur
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.

Pilote Sciences des écosystèmes et des océans Perception et compréhension Vision par ordinateur
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.

Pilote Sciences des écosystèmes et des océans Perception et compréhension Vision par ordinateur
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

Pilote Sciences des écosystèmes et des océans Perception et compréhension Vision par ordinateur
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.

Pilote Sciences des écosystèmes et des océans Perception et compréhension Vision par ordinateur
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.

Pilote Sciences des écosystèmes et des océans Perception et compréhension Vision par ordinateur
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.

Pilote Sciences des écosystèmes et des océans Perception et compréhension Vision par ordinateur
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.

Pilote Sciences des écosystèmes et des océans Perception et compréhension Vision par ordinateur
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.

Pilote Sciences des écosystèmes et des océans Perception et compréhension Vision par ordinateur
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.

Pilote Sciences des écosystèmes et des océans Perception et compréhension Vision par ordinateur
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.

Pilote Sciences des écosystèmes et des océans Perception et compréhension Vision par ordinateur
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.

Pilote Sciences des écosystèmes et des océans Perception et compréhension Vision par ordinateur
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.

Pilote Sciences des écosystèmes et des océans Perception et compréhension Vision par ordinateur
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.

Pilote Sciences des écosystèmes et des océans Perception et compréhension Vision par ordinateur
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.

Pilote Dirigeant principal du numérique Perception et compréhension Vision par ordinateur