20 citations · 48 across the 11 of their papers we have counts for
4 papers · 1 filter
Euclid Quick Data Release (Q1). AstroVink: A vision transformer approach to find strong gravitational lens systems
Euclid Collaboration, S. H. Vincken, K. Rojas +302
We present AstroVink, a vision transformer classifier designed for automated identification of strong lens candidates in Euclid imaging. We build upon the DINOv2 encoder, fine tune…
Reducing false positives in strong lens detection through effective augmentation and ensemble learning
Samira Rezaei, Amirmohammad Chegeni, Bharath Chowdhary Nagam +4
This research studies the impact of high-quality training datasets on the performance of Convolutional Neural Networks (CNNs) in detecting strong gravitational lenses. We stress th…
Euclid: Searches for strong gravitational lenses using convolutional neural nets in Early Release Observations of the Perseus field
R. Pearce-Casey, B. C. Nagam, J. Wilde +204
The Euclid Wide Survey (EWS) is predicted to find approximately 170 000 galaxy-galaxy strong lenses from its lifetime observation of 14 000 deg^2 of the sky. Detecting this many le…
Object classification with Convolutional Neural Networks: from KiDS to Euclid
G. A. Verdoes Kleijn, C. A. Marocico, Y. Mzayek +11
Large-scale imaging surveys have grown about 1000 times faster than the number of astronomers in the last 3 decades. Using Artificial Intelligence instead of astronomer's brains fo…