12 citations · 27 across the 11 of their papers we have counts for
11 papers
NEEDL-Bench: Dataset for Swiss Needle Cast and Stomata Detection in Microscopy Images
Benjamin Blake, Declan McIntosh, Jürgen Ehlting +3
We present NEEDL-Bench, a microscopy detection benchmark for Swiss Needle Cast (SNC), a fungal disease of Douglas-fir trees. Douglas-fir is a keystone species of major ecological a…
TubeLite: Lightweight Multi-Actor Spatio-Temporal Action Detection
Ali Soltaninezhad, Melissa Cote, Alejandro Rico Espinosa +2
Spatio-temporal action detection in videos requires jointly localizing actors in space and identifying action boundaries over time. A common challenge is constructing temporally st…
BAAF: Universal Transformation of One-Class Classifiers for Unsupervised Image Anomaly Detection
Declan McIntosh, Alexandra Branzan Albu
Detecting anomalies in images and video is an essential task for multiple real-world problems, including industrial inspection, computer-assisted diagnosis, and environmental monit…
Exploring text-to-image generation for historical document image retrieval
Melissa Cote, Alexandra Branzan Albu
Attribute-based document image retrieval (ABDIR) was recently proposed as an alternative to query-by-example (QBE) searches, the dominant document image retrieval (DIR) paradigm. O…
A Data-Driven Approach for Finding Requirements Relevant Feedback from TikTok and YouTube
Manish Sihag, Ze Shi Li, Amanda Dash +5
The increasing importance of videos as a medium for engagement, communication, and content creation makes them critical for organizations to consider for user feedback. However, si…
TempNet: Temporal Attention Towards the Detection of Animal Behaviour in Videos
Declan McIntosh, Tunai Porto Marques, Alexandra Branzan Albu +2
Recent advancements in cabled ocean observatories have increased the quality and prevalence of underwater videos; this data enables the extraction of high-level biologically releva…
Preservation of High Frequency Content for Deep Learning-Based Medical Image Classification
Declan McIntosh, Tunai Porto Marques, Alexandra Branzan Albu
Chest radiographs are used for the diagnosis of multiple critical illnesses (e.g., Pneumonia, heart failure, lung cancer), for this reason, systems for the automatic or semi-automa…
Movement Tracks for the Automatic Detection of Fish Behavior in Videos
Declan McIntosh, Tunai Porto Marques, Alexandra Branzan Albu +2
Global warming is predicted to profoundly impact ocean ecosystems. Fish behavior is an important indicator of changes in such marine environments. Thus, the automatic identificatio…
Symbol Spotting on Digital Architectural Floor Plans Using a Deep Learning-based Framework
Alireza Rezvanifar, Melissa Cote, Alexandra Branzan Albu
This papers focuses on symbol spotting on real-world digital architectural floor plans with a deep learning (DL)-based framework. Traditional on-the-fly symbol spotting methods are…
L^2UWE: A Framework for the Efficient Enhancement of Low-Light Underwater Images Using Local Contrast and Multi-Scale Fusion
Tunai Porto Marques, Alexandra Branzan Albu
Images captured underwater often suffer from suboptimal illumination settings that can hide important visual features, reducing their quality. We present a novel single-image low-l…
A Deep Learning-based Framework for the Detection of Schools of Herring in Echograms
Alireza Rezvanifar, Tunai Porto Marques, Melissa Cote +6
Tracking the abundance of underwater species is crucial for understanding the effects of climate change on marine ecosystems. Biologists typically monitor underwater sites with ech…