Faculty profile
Alexandra Branzan Albu
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Research
Latest papers
Label-Free Tracking of Proteins through Plasmon-Enhanced Interference.
ACS nanoscience Au · 2024
Automatic segmentation and tracking of biological prosthetic heart valves.
Journal of medical imaging (Bellingham, Wash.) · 2021 · senior author
A Contrast-Guided Approach for the Enhancement of Low-Lighting Underwater Images.
Journal of imaging · 2019
Latest funding
- $160,000
Towards Sustainable Fisheries: Computer Vision Methods for the Automatic Analysis of Fishing Imagery
NSERC · 2023 · Principal investigator
- $72,000
Computer Vision Methods for Marine Ecology
NSERC · 2022 · Principal investigator
- $60,000
Computer Vision-Based Deep Learning Algorithms for Detecting Marine Life and Physical Phenomena from Acoustic Backscatter Time Series
NSERC · 2022 · Principal investigator
4 publications.
Label-Free Tracking of Proteins through Plasmon-Enhanced Interference.
Peters M, McIntosh D, Branzan Albu A, Ying C, Gordon R
Automatic segmentation and tracking of biological prosthetic heart valves.
Alizadeh M, Cote M, Branzan Albu A
A Contrast-Guided Approach for the Enhancement of Low-Lighting Underwater Images.
Porto Marques T, Branzan Albu A, Hoeberechts M
Local image enhancement for fiducial marker detection in electronic portal images of prostate radiotherapy.
Bonneau P, Branzan Albu A, Hilts M
Towards Sustainable Fisheries: Computer Vision Methods for the Automatic Analysis of Fishing Imagery
Principal investigators: Branzan Albu, Alexandra A
Keywords: action recognition; automatic detection; computer vision; deep learning; electronic monitoring; image processing; pattern recognition; sustainable fisheries; video processing and analysis; video summarization
Computer Vision Methods for Marine Ecology
Principal investigators: Branzan-Albu, Alexandra
Keywords: image processing; pattern recognition; computer vision; machine learning; deep learning; object recognition; semantic segmentation; instance segmentation; video analysis; event detection
Computer Vision-Based Deep Learning Algorithms for Detecting Marine Life and Physical Phenomena from Acoustic Backscatter Time Series
Principal investigators: Branzan Albu, Alexandra A
Keywords: acoustic imaging; automatic detection; computer vision; deep learning; digital signal processing; image processing; multi-frequency echograms; pattern recognition; semantic segmentation; underwater acoustic data
Automatic Visual Analysis of Acoustic Backscatter Time Series for Monitoring Underwater Environments_x000d_
Principal investigators: Branzan Albu, Alexandra
Computer vision-based detection of marine vessels in the Canadian Arctic using visual and acoustic data_x000d_
Principal investigators: Branzan Albu, Alexandra
Computer vision and machine learning algorithms for detecting marine life from acoustic backscatter time series
Principal investigators: BranzanAlbu, Alexandra
Mobile computer vision system for document image rendering, manipulation, and management on collaborative e-writing devices
Principal investigators: Branzan Albu, Alexandra
Computer vision-based detection of fish from acoustic backscatter time series
Principal investigators: BranzanAlbu, Alexandra
Computer vision methods for image rendering and manipulation on e-writing devices
Principal investigators: BranzanAlbu, Alexandra
Computer vision-based part number recognition for optimized off-logging processes
Principal investigators: BranzanAlbu, Alexandra
From CIHR, NSERC and SSHRC funding decisions: CIHR since 2008, NSERC since 1991 and SSHRC since 1998, including their latest published competition results.
Frequent collaborators
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