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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63 current initiative(s)

AI initiative registry
ID	AI Initiative	Stage	Description	Sector	Region	AI Bucket	SME
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 Computer Vision	Sastri, Akash
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 Computer Vision	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 Computer Vision	Bird, Tom
62	Deep sea habitat, organism and object detection and identification.	Ideation	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 Computer Vision	Best, Merlin
58	Phytoplankton image classification model	Pilot	Create a neural network model to classify phytoplankton images collected by in-situ phytoplankton imaging sensors. There are two discrete s...	Ecosystems and Oceans Science	Pacific	Perception and Understanding Computer Vision	Covert, Paul
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 Computer Vision	Quan, Eric
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 Computer Vision	Quan, Eric
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 Computer Vision	Legresley, Jean-Claude
35	AI-assisted Solution to Detect Ghost Gear from Side Scan Sonar Images	Ideation 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 Computer Vision	Petrovic, Marina
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 Computer Vision	Wang, Yuchen
33	Machine-learning-assisted Benthic Marine Life Annotation Tool	Ideation On hold On hold	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...	Strategic Policy	National Capital Region	Perception and Understanding Computer Vision	Wang, Yuchen
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 Computer Vision	Spearin, Brendan
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 Computer Vision	Bédard, Mathieu

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 Computer Vision
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 Computer Vision
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 Computer Vision
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.

Ideation Ecosystems and Oceans Science Perception and Understanding Computer Vision
58
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. Convolutional Neural Network, InceptionV3 and ResNet

Pilot Ecosystems and Oceans Science Perception and Understanding Computer Vision
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 Computer Vision
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 Computer Vision
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 Computer Vision
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

Ideation On hold Strategic Policy Perception and Understanding Computer Vision
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 Computer Vision
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

Ideation On hold Strategic Policy Perception and Understanding Computer Vision
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 Computer Vision
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 Computer Vision