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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146 current initiative(s)

AI initiative registry
ID	AI Initiative	Current Status	Description	Sector	Region	AI Bucket	SME
95	Optimization of Machine Learning modelling strategy for coastal zooplankton taxonomic identification from flow microscopy imaging.	Pilot	As part of Aquaculture Monitoring Program we are using Ecotaxa's ML algorithm to identify zooplankton. The project aims at identifying the b...	Ecosystems and Oceans Science	National Capital Region	Perception and Understanding	Winegardner, Amanda
94	DFO Bot, deep learning application to analyse otolith images available in DFO Dots	Pilot	Development of a neural network trained using otolith images, expert-derived age estimates, otolith annotations and annuli to obtain age est...	Ecosystems and Oceans Science	National Capital Region	Perception and Understanding	Winegardner, Amanda
93	Détection de homards et de crabes communs dans les images sous-marines par intelligence artificielle.	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	Winegardner, Amanda
92	Identification automatisée de la condition de carapace de crabe des neiges	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	Winegardner, Amanda
91	Localization and Tracking of Beluga Whales in Aerial video Using Deep Learning	Pilot	Deep-learning model was developed us YOLOv7 to detect beluga whales from imagery footage. The main contribution of this research is providin...	Ecosystems and Oceans Science	National Capital Region	Perception and Understanding	Winegardner, Amanda
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
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
88	Development of an AI matching model for bowhead whale photo-identification	Pilot	Using DFO’s existing database of bowhead whale photographs, the specific objectives are: 1) Create a machine learning model “detector” for b...	Ecosystems and Oceans Science	National Capital Region	Perception and Understanding	Winegardner, Amanda
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
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
85	Daily Use	Pilot	Bing CoPilot, ChatGPT-4 Emails, documents, speaking points, ideas	Programs Sector	National Capital Region	Cognitive and Generative AI	Newman, Candace
84	Daily Use	Pilot	Dashboard Development, Used the standalone M365 version of Copilot to assist with coding.	Programs Sector	National Capital Region	Cognitive and Generative AI	Newman, Candace
83	Daily Use	Pilot	Mapping, The AI Assist function in FME has been used to support code development for data processing while integrating and manipulating data...	Programs Sector	National Capital Region	Automation and Decision Support	Newman, Candace
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
80	Various Built-In AI Features (Co-pilot, ChatGPT, etc)	Pilot	Using built-in AI features and functions in regular workflow operations. This includes LLM's such as ChatGPT, Microsoft Copilot, Gemini, and...	Ecosystems and Oceans Science	Pacific	Cognitive and Generative AI	Quan, Eric
78	Okanagan sockeye life cycle model	Pilot	Using LLM (ChatGPT) to support the development of a statistical lifecycle model for Okanagan sockeye. LLMs are not developing the models but...	Ecosystems and Oceans Science	Pacific	Cognitive and Generative AI	Thompson, Patrick
74	Pacific Plankton Monitoring: Imagery and automated classification	Pilot	• Monitoring of zooplankton and phytoplankton in the water column with shipboard and benchtop plankton imaging instruments (UVP, ZooScan, Pl...	Ecosystems and Oceans Science	Pacific	Perception and Understanding	Sastri, Akash
70	Data Validation Tool (See B6, B22)	Pilot	Use large language models to help detect errors in data transcribed using optical character recognition. Apply validation rules to propose...	Ecosystems and Oceans Science	Pacific	Automation and Decision Support	Bird, Tom
69	Species distribution modeling	Pilot	Species distribution models for various coral/sponge/groundfish Random Forests	Ecosystems and Oceans Science	Pacific	Automation and Decision Support	Rooper, Chris
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
66	Optical Character Recognition Data transcription tool (See B6, B26)	Pilot	Built a proof of concept tool to facilitate data transcription and validation from hand-written field notes. Tested on ~100 year old salmon...	Ecosystems and Oceans Science	Pacific	Perception and Understanding	Bird, Tom
65	Comprehensive marine substrate classification applied to Canada’s Pacific shelf	Pilot	We built five regional and one coastwide substrate model for the BC coast using substrate observations and seafloor bathymetry derivatives a...	Ecosystems and Oceans Science	Pacific	Automation and Decision Support	Haggarty, Dana
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
63	Factoid Finder Tool	Pilot	The Factoid Finder extracts text from machine-readable PDFs to create searchable content libraries. Small Language Models are used to implem...	—	Pacific	Cognitive and Generative AI	Caron, Chantelle
61	CTD data QC using ML	Pilot	Working with CDOS office to streamline our CTD QC using ML cnn and others	Ecosystems and Oceans Science	Pacific	Automation and Decision Support	Guan, Lu

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.

Pilot Ecosystems and Oceans Science Perception and Understanding
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.

Pilot Ecosystems and Oceans Science Perception and Understanding
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
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
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.

Pilot Ecosystems and Oceans Science 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
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
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.

Pilot Ecosystems and Oceans Science 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
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
85
Daily Use
Bing CoPilot, ChatGPT-4 Emails, documents, speaking points, ideas

Pilot Programs Sector Cognitive and Generative AI
84
Daily Use
Dashboard Development, Used the standalone M365 version of Copilot to assist with coding.

Pilot Programs Sector Cognitive and Generative AI
83
Daily Use
Mapping, The AI Assist function in FME has been used to support code development for data processing while integrating and manipulating data in workbenches.

Pilot Programs Sector Automation and Decision Support
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
80
Various Built-In AI Features (Co-pilot, ChatGPT, etc)
Using built-in AI features and functions in regular workflow operations. This includes LLM's such as ChatGPT, Microsoft Copilot, Gemini, and various others that are integrated directly into the applications already currently being used. Large Language Models

Pilot Ecosystems and Oceans Science Cognitive and Generative AI
78
Okanagan sockeye life cycle model
Using LLM (ChatGPT) to support the development of a statistical lifecycle model for Okanagan sockeye. LLMs are not developing the models but are used to brainstorm modelling approaches, debug code, and confirm that written model descriptions in manuscripts are accurate and clear. AI is not being tasked with developing these models. Large Language Models

Pilot Ecosystems and Oceans Science Cognitive and Generative AI
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.

Pilot Ecosystems and Oceans Science Perception and Understanding
70
Data Validation Tool (See B6, B22)
Use large language models to help detect errors in data transcribed using optical character recognition. Apply validation rules to propose corrections and normalize data into a standardized format. (Digitizing non-machine-readable (handwritten) documents and extracts characters into a digital format) Llama 3.0 Large Language Model

Pilot Ecosystems and Oceans Science Automation and Decision Support
69
Species distribution modeling
Species distribution models for various coral/sponge/groundfish Random Forests

Pilot Ecosystems and Oceans Science Automation and Decision Support
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
66
Optical Character Recognition Data transcription tool (See B6, B26)
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 determin ethe cost/feasibility/effectiveness of implementing such a tool in Salmon monitoring contexts. (Digitizing non-machine-readable (handwritten) documents and extracts characters into a digital format) Computer vision (azure document intelligence),

Pilot Ecosystems and Oceans Science Perception and Understanding
65
Comprehensive marine substrate classification applied to Canada’s Pacific shelf
We built five regional and one coastwide substrate model for the BC coast using substrate observations and seafloor bathymetry derivatives and oceanographic predictors using Random Forests. Random Forests

Pilot Ecosystems and Oceans Science Automation and Decision Support
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
63
Factoid Finder Tool
The Factoid Finder extracts text from machine-readable PDFs to create searchable content libraries. Small Language Models are used to implement semantic search techniques, allowing users to search the library for relevant passages within the PDFs. Small Language Model and Text Embedder: MS Marco Distilbert Dot-v5 Cross-encoder: MS Marco MiniLM-L6-v2

Pilot Cognitive and Generative AI
61
CTD data QC using ML
Working with CDOS office to streamline our CTD QC using ML cnn and others

Pilot Ecosystems and Oceans Science Automation and Decision Support