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ground_lastro_epfl_100epochs.h5 (65.11 MB)
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ground_lastro_epfl_250epochs.h5 (65.11 MB)
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ground_lens_finder_50epochs.h5 (118.15 MB)
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ground_lens_finder_100epochs.h5 (118.15 MB)
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ground_lens_finder_250epochs.h5 (118.15 MB)
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ground_lens_flow_50epochs.h5 (1.2 MB)
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ground_lens_flow_100epochs.h5 (1.2 MB)
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ground_lens_flow_250epochs.h5 (1.2 MB)
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ground_wsi_net_50epochs.h5 (30.09 MB)
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ground_wsi_net_100epochs.h5 (30.09 MB)
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ground_wsi_net_250epochs.h5 (30.09 MB)
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space_cas_swinburne_5epochs.h5 (46.12 MB)
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space_cas_swinburne_10epochs.h5 (46.12 MB)
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space_cas_swinburne_25epochs.h5 (46.12 MB)
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space_cas_swinburne_50epochs.h5 (46.12 MB)
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space_cas_swinburne_75epochs.h5 (46.12 MB)
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space_cas_swinburne_100epochs.h5 (46.12 MB)
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space_cas_swinburne_250epochs.h5 (46.12 MB)
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space_cmu_deeplens_5epochs.h5 (41.12 MB)
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space_cmu_deeplens_10epochs.h5 (41.12 MB)
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LEXACTUM trained model weights
dataset
posted on 2024-07-12, 07:22 authored by DANIEL MAGRO, KRISTIAN ZARB ADAMIKRISTIAN ZARB ADAMI, Andrea De MarcoAndrea De Marco, Simone Riggi, Eva SciaccaThese files are the weights from the models described in our paper, "Convolutional Neural Networks for the Automated Detection of Strong Gravitational Lensing" (https://academic.oup.com/mnras/article/505/4/6155/6295319), trained for a varying number of epochs.
The dataset on which these models have been trained is available on the Gravitational Lens Finding Challenge 1.0 web page:
http://metcalf1.difa.unibo.it/blf-portal/gg_challenge.html
The code written to train and load these models is available on the GitHub repository:
https://github.com/DanielMagro97/LEXACTUM
These models were also previously uploaded to, and are accessible on, Zenodo:
https://zenodo.org/records/4299924
