migYOLO - An end-to-end YOLOv8-based object detection pipeline for CMOS camera images recorded by the MIGDAL experiment

migYOLO v1.0.0 migYOLO is the software accompanying the MIGDAL collaboration paper titled Transforming a rare event search into a not-so-rare event search in real-time with deep learning-based object detection . This package includes model weights for two YOLOv8m models custom trained on image data...

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Bibliographic Details
Main Author: Schueler, Jeffrey
Format: Other/Unknown Material
Language:English
Published: Zenodo 2024
Subjects:
Python3
YOLOv8
Deep Learning
Object Detection
Migdal Effect
Dark Matter
MIGDAL Experiment
Orca
Online Access:https://doi.org/10.5281/zenodo.12628437
id ftzenodo:oai:zenodo.org:12628437
record_format openpolar
spelling ftzenodo:oai:zenodo.org:12628437 2024-09-15T18:28:54+00:00 migYOLO - An end-to-end YOLOv8-based object detection pipeline for CMOS camera images recorded by the MIGDAL experiment Schueler, Jeffrey 2024-07-02 https://doi.org/10.5281/zenodo.12628437 eng eng Zenodo https://github.com/jschuel/migYOLO/tree/v1.0.0 https://arxiv.org/abs/arXiv:2406.07538 https://migyolo.readthedocs.io/en/latest/index.html https://doi.org/10.5281/zenodo.12628436 https://doi.org/10.5281/zenodo.12628437 oai:zenodo.org:12628437 info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode Python3 YOLOv8 Deep Learning Object Detection Migdal Effect Dark Matter MIGDAL Experiment info:eu-repo/semantics/other 2024 ftzenodo https://doi.org/10.5281/zenodo.1262843710.5281/zenodo.12628436 2024-07-26T12:57:45Z migYOLO v1.0.0 migYOLO is the software accompanying the MIGDAL collaboration paper titled Transforming a rare event search into a not-so-rare event search in real-time with deep learning-based object detection . This package includes model weights for two YOLOv8m models custom trained on image data recorded by the ORCA Quest qCMOS camera readout of the MIGDAL TPC, as well as a sample of 800 raw camera images to demonstrate usage of the pipeline, and 400 additional camera frames for benchmarking the processing speed of the camera. Please consult the migYOLO git repository and official documentation for more detailed descriptions of the software package and its contents, as well as up to date information about installation and usage. Other/Unknown Material Orca Zenodo
institution Open Polar
collection Zenodo
op_collection_id ftzenodo
language English
topic Python3
YOLOv8
Deep Learning
Object Detection
Migdal Effect
Dark Matter
MIGDAL Experiment
spellingShingle Python3
YOLOv8
Deep Learning
Object Detection
Migdal Effect
Dark Matter
MIGDAL Experiment
Schueler, Jeffrey
migYOLO - An end-to-end YOLOv8-based object detection pipeline for CMOS camera images recorded by the MIGDAL experiment
topic_facet Python3
YOLOv8
Deep Learning
Object Detection
Migdal Effect
Dark Matter
MIGDAL Experiment
description migYOLO v1.0.0 migYOLO is the software accompanying the MIGDAL collaboration paper titled Transforming a rare event search into a not-so-rare event search in real-time with deep learning-based object detection . This package includes model weights for two YOLOv8m models custom trained on image data recorded by the ORCA Quest qCMOS camera readout of the MIGDAL TPC, as well as a sample of 800 raw camera images to demonstrate usage of the pipeline, and 400 additional camera frames for benchmarking the processing speed of the camera. Please consult the migYOLO git repository and official documentation for more detailed descriptions of the software package and its contents, as well as up to date information about installation and usage.
format Other/Unknown Material
author Schueler, Jeffrey
author_facet Schueler, Jeffrey
author_sort Schueler, Jeffrey
title migYOLO - An end-to-end YOLOv8-based object detection pipeline for CMOS camera images recorded by the MIGDAL experiment
title_short migYOLO - An end-to-end YOLOv8-based object detection pipeline for CMOS camera images recorded by the MIGDAL experiment
title_full migYOLO - An end-to-end YOLOv8-based object detection pipeline for CMOS camera images recorded by the MIGDAL experiment
title_fullStr migYOLO - An end-to-end YOLOv8-based object detection pipeline for CMOS camera images recorded by the MIGDAL experiment
title_full_unstemmed migYOLO - An end-to-end YOLOv8-based object detection pipeline for CMOS camera images recorded by the MIGDAL experiment
title_sort migyolo - an end-to-end yolov8-based object detection pipeline for cmos camera images recorded by the migdal experiment
publisher Zenodo
publishDate 2024
url https://doi.org/10.5281/zenodo.12628437
genre Orca
genre_facet Orca
op_relation https://github.com/jschuel/migYOLO/tree/v1.0.0
https://arxiv.org/abs/arXiv:2406.07538
https://migyolo.readthedocs.io/en/latest/index.html
https://doi.org/10.5281/zenodo.12628436
https://doi.org/10.5281/zenodo.12628437
oai:zenodo.org:12628437
op_rights info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
op_doi https://doi.org/10.5281/zenodo.1262843710.5281/zenodo.12628436
_version_ 1810470338079752192

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