12 citations · 26 across the 6 of their papers we have counts for
6 papers
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…
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…
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…