Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T22:56:21.395882Z
Paper Citation Record · LEDGER
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model
As of 21 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 0 inbound Pith citation observations for arXiv:2501.00380.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
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Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
60 of 60 outbound references displayed
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External citation measurements
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Outbound references
Observation f721c609-57d7-4abc-ba4a-2ee28168d78d · outbound
This paper cites A., Huang, R., & Ananthi, P.
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model A., Huang, R., & Ananthi, P
Reference 1
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Observation 4e26efd2-06f0-452d-b03a-91bae1ff39f0 · outbound
This paper cites M., Loveday, J., & Brunner, R.
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model M., Loveday, J., & Brunner, R
Reference 2
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Observation a66590be-5541-4746-9a7d-407da46544cb · outbound
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An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model Y ., Mcintosh, D
Reference 4
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Observation bfee916f-8ee4-4fb6-a2fc-25cf4ef299bf · outbound
This paper cites B., van Dokkum, P.
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model B., van Dokkum, P
Reference 5
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Observation 78697bc1-cf21-4ee6-94bd-dcb2762ea7a7 · outbound
This paper cites 2020, in Proceedings of the 34th Interna- tional Conference on Neural Information Processing Systems, NIPS ’20 (Red.
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model 2020, in Proceedings of the 34th Interna- tional Conference on Neural Information Processing Systems, NIPS ’20 (Red
Reference 7
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Observation a7918a6d-1b70-4194-a237-3a36dc8ea674 · outbound
This paper cites 2020, in Proceedings of the 37th International Conference on Machine Learning, ICML’20 (JMLR.org).
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model 2020, in Proceedings of the 37th International Conference on Machine Learning, ICML’20 (JMLR.org)
Reference 8
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An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model Unresolved cited work
Reference 11
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Observation 82c7a0f9-b585-4c05-8141-2982ca72a5af · outbound
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An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model Unresolved cited work
Reference 12
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Observation 8157cc5f-fd71-4f2e-9f8a-6f09d1f1ce36 · outbound
This paper cites J., Bershady, M.
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model J., Bershady, M
Reference 13
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Observation 80219dec-3aac-4656-8157-1bfa71ede308 · outbound
This paper cites J., Rajgor, S., & Myers, R.
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model J., Rajgor, S., & Myers, R
Reference 14
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Observation 72a40521-dbb2-45b8-a144-faa06dd3b637 · outbound
This paper cites 2023, ApJS, 268, 34.
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model 2023, ApJS, 268, 34
Reference 15
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Observation a9335940-6769-4de3-90ef-d1c013c7b92b · outbound
This paper cites W., & Dambre, J.
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model W., & Dambre, J
Reference 16
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Observation 7a4b4e48-e3b9-4e01-8d67-5b7f3e510244 · outbound
This paper cites 2021, in 9th International Con- ference on Learning Representations, ICLR 2021, Virtual Event, Austria, May 3-7, 2021 (OpenReview.net).
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model 2021, in 9th International Con- ference on Learning Representations, ICLR 2021, Virtual Event, Austria, May 3-7, 2021 (OpenReview.net)
Reference 17
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Observation 76d5e7e1-f353-45b3-a452-b0f693ad44fb · outbound
This paper cites C., & Hospedales, T.
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model C., & Hospedales, T
Reference 18
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Observation 28b7bd35-2fc0-494a-9acd-36aa8b257308 · outbound
This paper cites 2023, AJ, 165, 35.
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model 2023, AJ, 165, 35
Reference 19
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Observation 23742433-1441-4fc9-9503-f311d1cca2ea · outbound
This paper cites E., Izbicki, R., Lee, A.
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model E., Izbicki, R., Lee, A
Reference 20
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Observation 3692c416-b907-4e42-8f85-d4019c07265a · outbound
This paper cites M., Wang, Z., et al.
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model M., Wang, Z., et al
Reference 21
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Observation 7b172f33-20c9-49ce-93f6-aeac74e3c563 · outbound
This paper cites 2018, AJ, 855, 10.
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model 2018, AJ, 855, 10
Reference 22
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Observation e86bf7d3-ae5e-4fcc-aeff-64db704097b6 · outbound
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An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model Unresolved cited work
Reference 23
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Observation 4f73ead4-a55a-42d9-a348-6b5a891f36ff · outbound
This paper cites 2016, in 2016 IEEE Conference on Com- puter Vision and Pattern Recognition (CVPR), 770–778.
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model 2016, in 2016 IEEE Conference on Com- puter Vision and Pattern Recognition (CVPR), 770–778
Reference 24
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This paper cites An Unsupervised Deep-Learning Method for Fingerprint Classification: the CCAE Network and the Hybrid Clustering Strategy.
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model An Unsupervised Deep-Learning Method for Fingerprint Classification: the CCAE Network and the Hybrid Clustering Strategy
Reference 25
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Observation b76197e5-aab8-4752-ae7e-4bdafc4482cc · outbound
This paper cites 2008, ApJ, 690, 1236.
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model 2008, ApJ, 690, 1236
Reference 26
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Observation e839961a-543b-4ea6-801c-6f23bf657eaf · outbound
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This paper cites S., Rose, C., Vanderhoof, B.
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model S., Rose, C., Vanderhoof, B
Reference 28
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An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model M., Aussel, H., Calzetti, D., et al
Reference 29
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An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model M., Fruchter, A
Reference 30
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An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model Unresolved cited work
Reference 31
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This paper cites 2021, in 2021 IEEE/CVF International Conference on Computer Vision (ICCV), 9992–10002.
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model 2021, in 2021 IEEE/CVF International Conference on Computer Vision (ICCV), 9992–10002
Reference 32
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This paper cites 2022, in 2022 IEEE/CVF Conference on Com- puter Vision and Pattern Recognition (CVPR), 11966–11976.
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model 2022, in 2022 IEEE/CVF Conference on Com- puter Vision and Pattern Recognition (CVPR), 11966–11976
Reference 33
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Observation 044333c0-f585-41d2-89dd-5d43084e1b1f · outbound
This paper cites Simple but Effective Unsupervised Classification for Specified Domain Images: A Case Study on Fungi Images.
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model Simple but Effective Unsupervised Classification for Specified Domain Images: A Case Study on Fungi Images
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An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model M., Davis, M., Faber, S
Reference 35
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An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model M., Primack, J., & Madau, P
Reference 36
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This paper cites 2011, in Artificial Neural Networks and Machine Learning – ICANN 2011, ed.
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model 2011, in Artificial Neural Networks and Machine Learning – ICANN 2011, ed
Reference 37
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An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model 1983, The Computer Journal, 26, 354
Reference 38
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This paper cites Know Your Self-supervised Learning: A Survey on Image-based Generative and Discriminative Training.
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model Know Your Self-supervised Learning: A Survey on Image-based Generative and Discriminative Training
Reference 40
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Reference 42
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An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model 2020, Computation O ffloading in Mobile Edge Computing, ed
Reference 43
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Reference 44
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Reference 45
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Reference 46
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Observation 5b6cbd76-9461-45a1-8d23-2b4632000c90 · outbound
This paper cites R., de Carvalho, R.
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model R., de Carvalho, R
Reference 47
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Observation fd179b47-4b9f-44ee-b172-cbc42aae4cd8 · outbound
This paper cites 2021, IEEE Access, 9, 82146–82168.
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model 2021, IEEE Access, 9, 82146–82168
Reference 48
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An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model 2007, ApJS, 172, 1–8
Reference 49
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An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model 2024, ApJS, 272, 42
Reference 50
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An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model H., Bernardi, M., et al
Reference 52
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Observation 7237ac4a-dbd9-46f0-8092-929f4002c924 · outbound
This paper cites P., Conselice, C.
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model P., Conselice, C
Reference 53
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 29670027-a364-4e82-b7cc-bee93261c803 · outbound
This paper cites 2021, MNRAS, 506, 1927.
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model 2021, MNRAS, 506, 1927
Reference 54
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 013f73ee-5e5e-4336-8205-a09c67a1f5cc · outbound
This paper cites R., Kauffmann, O.
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model R., Kauffmann, O
Reference 55
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e0ce33e1-296a-4d94-b718-cdc0f8ef36f1 · outbound
This paper cites W., Lintott, C.
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model W., Lintott, C
Reference 56
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5e42d44f-8fec-4ef9-82f5-7db18e9c3af8 · outbound
This paper cites 2023, AJ, 954, 113.
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model 2023, AJ, 954, 113
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T22:56:21.504580Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 7d39322f-6ce4-43e1-af37-18d9713989a6 · outbound
This paper cites 1996, in Proceedings of the 1996 ACM SIGMOD International Conference on Management of Data, SIGMOD ’96 (New York, NY , USA: Association for Computing Machinery), 103–114.
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model 1996, in Proceedings of the 1996 ACM SIGMOD International Conference on Management of Data, SIGMOD ’96 (New York, NY , USA: Association for Computing Machinery), 103–114
Reference 58
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 90cb497d-e59a-4c15-994f-5a54a998f728 · outbound
This paper cites 2022, AJ, 163, 86.
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model 2022, AJ, 163, 86
Reference 59
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T22:56:21.480072Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 02c05c0a-7c2b-4246-9342-2242daed1647 · outbound
This paper cites 2019, Astrophysics and Space Science, 364 Article number, page 12 of 12.
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model 2019, Astrophysics and Space Science, 364 Article number, page 12 of 12
Reference 60
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Pith citing papers
No inbound Pith citation observations are available.