aalbu at uvic dot ca
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I am a Professor In Electrical and Computer Engineering at the University of Victoria, BC, Canada. My work involves teaching, research, and service within academic, professional and local communities.
I teach undergraduate and graduate courses related to signal processing, image processing, and computer vision. Read more...
My research is about Computer Vision, which is a field of Artificial Intelligence that focuses on pattern recognition from image and video data. Read more...
Recent Selected Publications (2021-2025)
Recent Selected Publications (2021-2025)
Journal Papers
Côté M* and Branzan-Albu A. (2024).
Attribute-Based Document Image Retrieval.
International Journal on Document Analysis and Recognition (IJDAR).
Côté M*, Dash A*, and Branzan-Albu A. (2024).
Semantic Segmentation of Textured Mosaics.
EURASIP Journal on Image and Video Processing.
Porto-Marques T*, Côté M*, Rezvanifar A*, Slonimer A*, Branzan-Albu A, Ersahin K, Gauthier S. (2022).
U-MSAA-Net: a Multi-Scale Additive Attention-Based Network for Pixel-Level Identification of Finfish and Krill in Echograms.
IEEE Journal of Oceanic Engineering.
Slonimer A*, Dosso S, Branzan-Albu A, Côté M*, Porto-Marques T*, Rezvanifar A*, Ersahin K, Mudge T, and Gauthier S. (2022).
Classification of Herring, Salmon, and Bubbles in Multi-Frequency Echograms using U-Net Neural Networks.
IEEE Journal of Oceanic Engineering.
Rezvanifar A*, Côté M*, and Branzan-Albu A. (2021).
Geometry-Based Symbol Spotting in Born-Digital Architectural Floor Plans.
SPIE Journal of Electronic Imaging.
Conference Papers
Cote M*, Dash A, Chawarski J, Branzan Albu A, Bharatkumar Senjaliya F*, Niemi A. (2025) Refining Naive Annotations with Limited Expert Guidance for Semantic Segmentation: A Case Study on Underwater Echograms. ICCV Joint Workshop on Marine Vision, (AAMVEM&CVAUI 2025) Honolulu, Oahu, USA.
Soltaninezhad A*, Cote M*, Espinosa AR*, Marques TP, Branzan Albu A, Paetkau J, Diaz V, & Lower J. (2025).
TrapCounter: Integrating Detection, Tracking and Optical Flow for the Automatic Counting of Active Fishing Traps.
IEEE Canadian Conference on Computer and Robot Vision(CRV 2025), Calgary, AB, Canada.
McIntosh D* and Branzan-Albu A. (2024).
Unsupervised, Online, and On-The-Fly Anomaly Detection for Non-Stationary Image Distributions.
European Conference on Computer Vision (ECCV 2024), Milan.
McIntosh D* and Branzan-Albu A. (2023).
Inter-Realization Channels: Unsupervised Anomaly Detection Beyond One-Class Classification.
International Conference on Computer Vision (ICCV 2023), Paris.
Rico Espinosa A*, McIntosh D*, Branzan-Albu A. (2023).
An Efficient Approach for Underwater Image Improvement: Deblurring, Dehazing, and Color Correction.
Winter Conference on Applications of Computer Vision (WACV 2023) Workshops, Waikoloa, Big Island, Hawaii, USA.
McIntosh D*, Porto-Marques T*, Branzan-Albu A, Rountree R, De Leo F. (2022).
TempNet: Temporal Attention Towards the Detection of Animal Behaviour in Videos.
International Conference on Pattern Recognition (ICPR 2022), Montreal, QC, Canada.
Slonimer A*, Cote M*, Porto Marques T*, Rezvanifar A*, Dosso S, Branzan-Albu A, Ersahin K, Mudge T and Gauthier S. (2022).
Instance Segmentation of Herring and Salmon Schools in Acoustic Echograms using a Hybrid U-Net.
IEEE Canadian Conference on Computer and Robot Vision (CRV 2022), Toronto, ON, Canada.
Dash A* and Branzan-Albu A*. (2022).
Classification of Handwritten Annotations in Mixed-Media Documents.
Conference on Robots and Vision (CRV 2022), Toronto, ON, Canada.
Alizadeh M*, Cote M*, Branzan-Albu A. (2022).
Towards Durability Estimation of Bioprosthetic Heart Valvesvia Motion Symmetry Analysis.
Winter Conference on Applications of Computer Vision (WACV 2022), Tucson, AZ, USA.
McIntosh D*, Porto Marques T*, Branzan Albu A. (2021).
Preservation of High Frequency Content for Deep Learning-Based Medical Image Classification.
IEEE Canadian Conference on Computer and Robot Vision (CRV 2021), Burnaby, BC, Canada.
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