papers

Publications (5)

cs.CV2022

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…

cs.CV2020

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…

eess.IV2022

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…

cs.CV2026

NEEDL-Bench: Dataset for Swiss Needle Cast and Stomata Detection in Microscopy Images

Benjamin Blake, Declan McIntosh, Jürgen Ehlting +3

The paper introduces NEEDL-Bench, a microscopy image dataset with annotations for detecting Swiss Needle Cast disease structures and stomata in Douglas-fir needles, and provides ba…

#microscopy#plant pathology#object detection#keypoint detection
cs.CV2026

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…