Registre des initiatives en IA

63 initiative(s) courante(s)

• 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

• 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)

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

• 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),

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

• 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.

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

• 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

  Pilote Sciences des écosystèmes et des océans 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

• 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