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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82 initiative(s)

Registre des initiatives en IA
ID	Initiative en IA	Statut actuel	Description	Secteur	Région	Catégorie d'IA	Expert en la matière
163	Recherches sur l’Intelligence artificielle pour le traitement automatisé des données d’acoustiques sous-marine Non traduit	Pilot	Nous utilisons les technologies d’apprentissage profond (deep learning) et les détecteurs pour la détection et identification en temps réal...	Sciences des écosystèmes et des océans	Région de la capitale nationale	Perception et compréhension	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. Non traduit	Idea	Projet de contribution avec le Centre de développement et de recherche en intelligence numérique (CDRIN). L’objectif est de concevoir et dév...	Sciences des écosystèmes et des océans	Région de la capitale nationale	Perception et compréhension	Winegardner, Amanda
161	Remote sensing of the internal tide in the St. Lawrence Non traduit	Pilot	Using model outputs (STLE500/STLE200) to 1) help identify internal tide surface signature in SWOT (Surface Water and Ocean Topography) data...	Sciences des écosystèmes et des océans	Région de la capitale nationale	Perception et compréhension	Winegardner, Amanda
159	Chumputer Vision - salmon scale age predictive AI Non traduit	Pilot	Deep Machine growth pattern Learning of chum salmon scales for predictive age assignments by way of scale pattern interpretation.	Sciences des écosystèmes et des océans	Région de la capitale nationale	Perception et compréhension	Winegardner, Amanda
157	Pacific Plankton Monitoring: Imagery and automated classification Non traduit	Pilot	1) Monitoring of zooplankton and phytoplankton in the water column with shipboard and benchtop plankton imaging instruments (UVP, ZooScan, P...	Sciences des écosystèmes et des océans	Région de la capitale nationale	Perception et compréhension	Winegardner, Amanda
154	Extracting impacts data from regulatory documents Non traduit	Pilot	Use OCR pdf readers, topic detection and language models to detect specific data elements inside written text documents, for extraction and...	Sciences des écosystèmes et des océans	Région de la capitale nationale	Perception et compréhension	Winegardner, Amanda
151	Zooplankton image analysis Non traduit	Pilot	Use Random Forest and residual neural networks (ResNet) for automated classification of zooplankton images collected using: 1) scanning of p...	Sciences des écosystèmes et des océans	Région de la capitale nationale	Perception et compréhension	Winegardner, Amanda
149	Nearshore biotopes model Non traduit	Pilot	Tools built in python to automate image analysis and fish measurement tasks. Applications include a conveyor belt camera and underwater towe...	Sciences des écosystèmes et des océans	Région de la capitale nationale	Perception et compréhension	Winegardner, Amanda
147	Optical Character Recognition Data transcription tool Non traduit	Pilot	This completed project built a proof of concept tool to facilitate data transcription and validation from hand-written field notes. tested...	Sciences des écosystèmes et des océans	Région de la capitale nationale	Perception et compréhension	Winegardner, Amanda
145	Automatic detection of unidentified fish sounds Non traduit	Pilot	This completed project used Random Forests and Convolutional Neural Networks (CNN) algorithms trained on manually detected fish sounds to de...	Sciences des écosystèmes et des océans	Région de la capitale nationale	Perception et compréhension	Winegardner, Amanda
143	Deep sea habitat, organism and object detection and identification. Non traduit	Pilot	Proposing a capstone project to Computer Science students from Camosun College to develop a pipeline for identifying objects and loading the...	Sciences des écosystèmes et des océans	Région de la capitale nationale	Perception et compréhension	Winegardner, Amanda
139	Phytoplankton image classification model Non traduit	Pilot	Create a neural network model to classify phytoplankton images collected by in-situ phytoplankton imaging sensors. There are two discrete s...	Sciences des écosystèmes et des océans	Région de la capitale nationale	Perception et compréhension	Winegardner, Amanda
132	Salmon Scale Aging Non traduit	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...	Sciences des écosystèmes et des océans	Région de la capitale nationale	Perception et compréhension	Winegardner, Amanda
130	Salmon Data Digitization Non traduit	Pilot	Digitizing non-machine-readable (handwritten) documents and extracts characters into a digital format so that it is accessible, editable, an...	Sciences des écosystèmes et des océans	Région de la capitale nationale	Perception et compréhension	Winegardner, Amanda
129	Salmon Fence Counting Non traduit	Pilot	A model using computer vision to analyze water stream fence video-footage, to simultaneously count the number of and predict the species of...	Sciences des écosystèmes et des océans	Région de la capitale nationale	Perception et compréhension	Winegardner, Amanda
126	Automated assessment of satellite imagery Non traduit	Pilot	AI routines are being developed and tested to assess large volume of satellite imagery and data to: i) Automatically Identify marine hazards...	Sciences des écosystèmes et des océans	Région de la capitale nationale	Perception et compréhension	Winegardner, Amanda
124	Development of an underwater videography and AI system for studying fish passage effectiveness Non traduit	Pilot	Designed to train existing DFO tools with information on fish passage effectiveness and develop an SOP for training videography-based AI mod...	Sciences des écosystèmes et des océans	Région de la capitale nationale	Perception et compréhension	Winegardner, Amanda
122	Development and testing of artificial intelligence and machine learning to analyze underwater photo and video data to assess marine impacts and resources Non traduit	Pilot	This completed project (2020/21) aimed to utilize machine learning and imaging technology in fisheries science. The proponent planned to use...	Sciences des écosystèmes et des océans	Région de la capitale nationale	Perception et compréhension	Winegardner, Amanda
119	Computer vision to automate fish data extraction from video Non traduit	Pilot	Our purpose has been to build a tool to broadly apply computer vision methods in marine research. Our work has generated several publication...	Sciences des écosystèmes et des océans	Région de la capitale nationale	Perception et compréhension	Winegardner, Amanda
118	Use of artificial intelligence models to facilitate seafloor video annotations in conservation areas. Non traduit	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...	Sciences des écosystèmes et des océans	Région de la capitale nationale	Perception et compréhension	Winegardner, Amanda
106	Finwave: an online photo-identification database and AI matching tool Non traduit	Pilot	This project aims to improve a publicly accessible machine learning platform capable of identifying individual killer whales in real-time...	Sciences des écosystèmes et des océans	Région de la capitale nationale	Perception et compréhension	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	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...	Sciences des écosystèmes et des océans	Région de la capitale nationale	Perception et compréhension	Winegardner, Amanda
104	Zooplankton classification from Video Plankton Recorder Non traduit	Pilot	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	Winegardner, Amanda
103	Improved understanding of the processes impacting harmful algal blooms Non traduit	Pilot	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	Winegardner, Amanda
100	Development of AI technology for otolith and scale ageing Non traduit	Pilot	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	Winegardner, Amanda

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 Sciences des écosystèmes et des océans Perception et compréhension
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 Sciences des écosystèmes et des océans Perception et compréhension
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 Sciences des écosystèmes et des océans Perception et compréhension
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 Sciences des écosystèmes et des océans Perception et compréhension
157
Pacific Plankton Monitoring: Imagery and automated classification
1) Monitoring of zooplankton and phytoplankton in the water column with shipboard and benchtop plankton imaging instruments (UVP, ZooScan, PlanktoScope). 2) 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.

Pilot Sciences des écosystèmes et des océans Perception et compréhension
154
Extracting impacts data from regulatory documents
Use OCR pdf readers, topic detection and language models to detect specific data elements inside written text documents, for extraction and analysis in a cumulative impacts context.

Pilot Sciences des écosystèmes et des océans Perception et compréhension
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 Sciences des écosystèmes et des océans Perception et compréhension
149
Nearshore biotopes model
Tools built in python to automate image analysis and fish measurement tasks. Applications include a conveyor belt camera and underwater towed stereo camera system.

Pilot Sciences des écosystèmes et des océans Perception et compréhension
147
Optical Character Recognition Data transcription tool
This completed project built a proof of concept tool to facilitate data transcription and validation from hand-written field notes. tested on ~100 year old salmon observations and present-day salmon stream inspection logs to determine the cost/feasibility/effectiveness of implementing such a tool in Salmon monitoring contexts.

Pilot Sciences des écosystèmes et des océans Perception et compréhension
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 Sciences des écosystèmes et des océans Perception et compréhension
143
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.

Pilot Sciences des écosystèmes et des océans Perception et compréhension
139
Phytoplankton image classification model
Create a neural network model to classify phytoplankton images collected by in-situ phytoplankton imaging sensors. There are two discrete steps to this project: 1) create a library of annotated images for model training; 2) creation and refinement of the CNN model.

Pilot Sciences des écosystèmes et des océans Perception et compréhension
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 Sciences des écosystèmes et des océans Perception et compréhension
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 Sciences des écosystèmes et des océans Perception et compréhension
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 Sciences des écosystèmes et des océans Perception et compréhension
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 Sciences des écosystèmes et des océans Perception et compréhension
124
Development of an underwater videography and AI system for studying fish passage effectiveness
Designed to train existing DFO tools with information on fish passage effectiveness and develop an SOP for training videography-based AI models in support of fish passage projects.

Pilot Sciences des écosystèmes et des océans Perception et compréhension
122
Development and testing of artificial intelligence and machine learning to analyze underwater photo and video data to assess marine impacts and resources
This completed project (2020/21) aimed to utilize machine learning and imaging technology in fisheries science. The proponent planned to use Video and Image Analytics for Marine Environments (VIAME), an open-source system developed by NOAA, for two specific purposes: 1. Measure the movement of Atlantic cod across boundaries at the Gilbert Bay Marine Protected Area in Newfoundland and Labrador. 2. Assess the impact of seismic surveying on Atlantic cod as part of a project funded by the Environmental Studies Research Fund (ESRF). The automatic detection and count of fish near MPA boundaries was expected to reduce use of personnel time and effort.

Pilot Sciences des écosystèmes et des océans Perception et compréhension
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 Sciences des écosystèmes et des océans Perception et compréhension
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 Sciences des écosystèmes et des océans Perception et compréhension
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 Sciences des écosystèmes et des océans Perception et compréhension
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 Sciences des écosystèmes et des océans Perception et compréhension
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 Sciences des écosystèmes et des océans Perception et compréhension
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 Sciences des écosystèmes et des océans Perception et compréhension
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 Sciences des écosystèmes et des océans Perception et compréhension