Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-02T05:58:49.782338Z
Paper Citation Record · LEDGER
As of 9 August 2026, this Paper Citation Record lists 87 of 87 outbound references and 0 inbound Pith citation observations for arXiv:2607.13192.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-02T05:58:49.782338Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
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
87 of 87 outbound references displayed
External citation measurements
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Observation 4f04a85d-f721-4118-ab82-9cd701d6708e · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? GPT-4 Technical Report
Reference 1
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Observation 5ec5b587-af49-4a0a-97c2-445190142c89 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? JGCL: Joint self-supervised and supervised graph contrastive learning
Reference 2
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Observation ad0fb807-3677-4f47-9815-824740b2d791 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? CrisisMMD: Multimodal twitter datasets from natural disasters
Reference 3
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Observation 1ab86eed-f9d0-4e4b-9a4d-66739e4dc899 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Flamingo: A visual language model for few-shot learning.Advances in neural information processing systems, 35: 23716–23736, 2022
Reference 4
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Observation 73716a63-e318-4c77-9738-337d9c2020a5 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Hyperspectral target detection using self-supervised background learning.Advances in Space Research, 74(2):628–646, 2024
Reference 5
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Observation c085dd17-1f15-4749-bcc0-61541368d3e3 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Robust and data-efficient generalization of self-supervised machine learning for diagnostic imaging.Nature Biomedical Engineering, 7(6):756–779, 2023
Reference 6
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Observation eae15a13-93c9-45df-84d3-d2489047da45 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? BEiT: BERT Pre-Training of Image Transformers
Reference 7
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Observation fc400826-bdad-426e-863a-519be6bc0539 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning
Reference 8
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Observation 75eb5ec4-e7f1-47d8-b1a7-62b7e2868c6b · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation Anchoring
Reference 9
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Observation ccbf8c50-6f53-4686-a02e-deedf42e885e · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Mixmatch: A holistic approach to semi-supervised learning.Advances in neural information processing systems, 32, 2019
Reference 10
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Observation fdf3a6f2-ac4d-433e-88cc-07098f7c051d · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Unsupervised learning of visual features by contrasting cluster assignments.Advances in neural information processing systems, 33:9912–9924, 2020
Reference 11
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Observation f3782da5-f387-43d2-a4e4-9d5df1bf7fb1 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Emerging properties in self-supervised vision transformers
Reference 12
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Observation b3c2e38f-0926-44b9-8504-063d9d348a57 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? A simple framework for contrastive learning of visual representations
Reference 13
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Observation e7d0fc89-8b13-4612-a58d-9e97e2f1636b · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Big self-supervised models are strong semi-supervised learners.Advances in neural information processing systems, 33:22243–22255, 2020
Reference 14
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Observation 39bc9793-986c-4f80-bd57-b36e8816963d · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Exploring simple siamese representation learning
Reference 15
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Observation 1ffdaa9d-fa1d-41d8-a4c6-3f75ba96d54a · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Not-so-supervised: a survey of semi-supervised, multi-instance, and transfer learning in medical image analysis.Medical image analysis, 54:280–296, 2019
Reference 16
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Observation 16eea5d2-7d11-4e78-8fed-2dfdc8c3e357 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Orienting novel 3D objects using self-supervised learning of rotation transforms
Reference 17
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Observation f9027b8b-d548-4e93-9521-6e7dc1360d41 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? BERT: Pre-training of deep bidirectional transformers for language understanding
Reference 18
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Observation 04388052-84bc-43a1-95d6-fc3554ac23df · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Unsupervised visual representation learning by context prediction
Reference 19
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Observation e59afc59-3600-4919-9a56-1ed362e9cc2f · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Self- supervised colorization towards monochrome-color camera systems using cycle cnn.IEEE Transactions on Image Processing, 30:6609–6622, 2021
Reference 20
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Observation 5d3e5796-69d3-40fb-854a-5ed61420e185 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Reference 21
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Observation e4449698-704a-4d96-9589-27bc9b20d1af · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Everingham, L
Reference 22
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Observation 9884dc30-2d89-4b94-9b07-970dec39d438 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? The Pascal Visual Object Classes (VOC) Challenge.International Journal of Computer Vision, 88(2):303–338, 2010
Reference 23
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Observation 1ae20ef1-cea9-414a-8ce0-1da4aeed6d2a · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Self-supervised representation learning by rotation feature decoupling
Reference 24
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Observation 6d43ea98-2d20-45d7-969d-c88015334ff6 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Bootstrap your own latent-a new approach to self-supervised learning.Advances in neural information processing systems, 33:21271–21284, 2020
Reference 25
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Observation 722ceb76-1875-48ed-9436-08b524ff9f8b · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? A survey on self-supervised learning: Algorithms, applications, and future trends.IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(12):9052–9071, 2024
Reference 26
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Observation 22c12c24-a931-4640-8325-ad6a5babe12b · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? CrisisKAN: Knowledge- infused and explainable multimodal attention network for crisis event classification
Reference 27
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Observation 0fbb8446-71d9-402d-bed7-594812cccfb9 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Skin Lesion Analysis toward Melanoma Detection: A Challenge at the International Symposium on Biomedical Imaging (ISBI) 2016, hosted by the International Skin Imaging Collaboration (ISIC)
Reference 28
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Observation 699cf1fe-94a8-43b1-8843-91a44b3f6962 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Deep residual learning for im- age recognition
Reference 29
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Observation e14f0da7-79d8-4031-82b6-d9857ea74d56 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Momentum contrast for unsupervised visual representation learning
Reference 30
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Observation acbf5561-e899-4f46-ba53-fba6508b51dd · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Masked autoencoders are scalable vision learners
Reference 31
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Observation 11d5e7cc-f570-4f4d-a47d-9148d18b2574 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Koniq-10k: An ecologically valid database for deep learning of blind image quality assessment.IEEE Transactions on Image Processing, 29:4041–4056, 2020
Reference 32
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Observation d3c546e5-c28c-4ba4-be31-650ccb256255 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Self-supervised learning by image colorization
Reference 33
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Observation 7dfe544f-02b6-43d4-a17b-62f2ab1f0c50 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Adco: Adversarial contrast for efficient learning of unsupervised representations from self-trained negative adversaries
Reference 34
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Observation a2436833-be00-434e-90d3-98e7dd655ed0 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Self-supervised color- concept association via image colorization.IEEE Transactions on Visualization and Computer Graphics, 29(1):247–256, 2022
Reference 35
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Observation 5f74a40e-2b05-40ff-97d7-aa8280872ab7 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Self-supervised, semi-supervised, multi-context learning for the combined classification and segmentation of medical images
Reference 36
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Observation 4bcd5fff-5654-4f9f-ab6c-539ab8a55049 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Scaling up visual and vision-language representation learning with noisy text supervision
Reference 37
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Observation 09af2bf8-0d83-493b-ad8c-10f83962a123 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Self-supervised visual feature learning with deep neural networks: A survey.IEEE transactions on pattern analysis and machine intelligence, 43(11): 4037–4058, 2020
Reference 38
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Observation 3dd24910-049a-46d0-9d0e-3709767f9aae · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Self-Supervised Spatiotemporal Feature Learning via Video Rotation Prediction
Reference 39
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Observation 02f74930-ed46-480c-a235-edb710a82936 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Learning multiple layers of features from tiny images
Reference 40
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Observation 5ca6a078-d1cc-4bfc-95b0-4326df54ca07 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Temporal Ensembling for Semi-Supervised Learning
Reference 41
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Observation 2ff3a332-9d50-4b64-9f65-5923be830961 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Hsieh, and Jang-Hwan Choi
Reference 42
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Observation 5f43b941-e784-4f26-9b4f-a05a26a16b6a · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? BLIP: Bootstrapping language- image pre-training for unified vision-language understanding and generation
Reference 43
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Observation 971d9c6d-1d2d-4f5a-8510-8c9e62bcccd1 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? BLIP-2: Bootstrapping language-image pre-training with frozen image encoders and large language models
Reference 44
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Observation aed19a3c-5a14-4b7e-9c1c-dfb095384388 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? KADID-10k: A large-scale artificially distorted IQA database
Reference 45
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Observation ab661813-795a-4f10-a264-3f1eb95fec14 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Microsoft coco: Common objects in context
Reference 46
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Observation 11ef7f89-7d0a-49c6-a4a1-24a1448614aa · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Visual instruction tuning.Advances in neural information processing systems, 36:34892–34916, 2023
Reference 47
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Observation c4d12fac-30a9-4f21-930a-32ad7830080e · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Self-supervised learning: Generative or contrastive.IEEE transactions on knowledge and data engineering, 35(1):857–876, 2021
Reference 48
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Observation a6d0a56f-bef7-4639-b0a5-3ec67398aae0 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Earthscape: A multi- modal dataset for surficial geologic mapping and earth surface analysis.arXiv preprint arXiv:2503.15625, 2025
Reference 49
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Observation e89f65d5-88bf-4c27-b1d8-2365464f0253 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Damage identification in social media posts using multimodal deep learning
Reference 50
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Observation c55a7495-ad46-44ff-8d43-083a37a7f08e · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Self-supervision for medical image classification: State-of-the-art performance with ˜100 labeled training samples per class.Bioengineering, 10(8):895, 2023
Reference 51
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Observation 5c81ba7b-006f-4ea0-8076-d59438d46d14 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Unsupervised learning of visual representations by solving jigsaw puzzles
Reference 52
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Observation 5511cfa4-0d96-4b4f-b651-8e5b0c66809b · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Real- istic evaluation of deep semi-supervised learning algorithms.Advances in neural information processing systems, 31, 2018
Reference 53
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Observation 32efa712-a4c4-4b65-a856-d30ea9d3e616 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Representation Learning with Contrastive Predictive Coding
Reference 54
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Observation 10ab5ff1-b0e6-4986-b309-3a37a9f25bd3 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? DINOv2: Learning Robust Visual Features without Supervision
Reference 55
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Observation 080963cc-3e33-4f17-bcc6-a4661fce2548 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Self-supervised learning through colorization for microscopy images
Reference 56
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Observation c5b09be1-fd33-44ae-94b3-98ec5ed1600b · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Context encoders: Feature learning by inpainting
Reference 57
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Observation 5d622989-8d6c-40f1-8343-3c5625a26091 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Kosmos-2: Grounding Multimodal Large Language Models to the World
Reference 58
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Observation ead4d0fe-e1a9-455f-8851-72283e4a00c2 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Learning transferable visual models from natural language supervision
Reference 59
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Observation ec1dbb94-723a-49fb-8ae6-4280f5fda365 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? High- resolution image synthesis with latent diffusion models
Reference 60
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Observation c471c8e9-4fc3-4ca5-8cc5-0dde0535fdb8 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? U-net: Convolutional networks for biomedical image segmentation
Reference 61
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Observation f8043861-2704-4160-9922-711bb63bfc26 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Unresolved cited work
Reference 62
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Observation 8cf0fbdf-633a-4c64-bceb-c242c763ae56 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Fixmatch: Simplifying semi- supervised learning with consistency and confidence.Advances in neural information processing systems, 33:596–608, 2020
Reference 63
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Observation 511a14c4-5359-4efb-9109-027cbd732e55 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Unresolved cited work
Reference 64
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Observation ac777ad1-065d-486a-b643-387c919ce046 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? What makes for good views for contrastive learning?Advances in neural information processing systems, 33:6827–6839, 2020
Reference 65
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Observation 9e52c98c-dd74-4aab-a43f-a0d9dd142309 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? YOLOv12: Attention-centric real-time object detectors.Advances in neural information processing systems, 38:78433–78457, 2025
Reference 66
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Observation b60855a1-4370-4027-9a5e-d4805549f22c · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Real-time self-supervised achromatic face colorization.The Visual Computer, 39(12):6521–6536, 2023
Reference 67
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Observation 9bf656eb-eb89-478f-a157-7ffd416eaf3d · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Toward a collective agenda on ai for earth science data analysis.IEEE Geoscience and Remote Sensing Magazine, 9(2):88–104, 2021
Reference 68
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Observation d63e8ab9-5aec-4d69-a75d-de6f93311cd1 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? A survey on semi-supervised learning.Machine learning, 109(2):373–440, 2020
Reference 69
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Observation 68b63625-a5d8-4bb0-b327-5ae87fbc20e7 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Optimizing area under the roc curve using semi-supervised learning
Reference 70
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Observation df41f95c-aeb5-4acb-9780-74debd35deb0 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Unsupervised learning of visual representations using videos
Reference 71
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Observation 1c15dbe6-33df-4295-9bda-d51023ed6579 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Unsupervised data aug- mentation for consistency training.Advances in neural information processing systems, 33: 6256–6268, 2020
Reference 72
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Observation 8f7a6ad4-2e9b-473d-8791-d59d3c825227 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Simmim: A simple framework for masked image modeling
Reference 73
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Observation 6414584d-b630-4a1d-98fc-cd07838aae9b · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Image enhanced rotation prediction for self-supervised learning
Reference 74
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Observation 0dbf9192-8061-4236-900e-04ea95d8fecf · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Self-supervised 3d action representation learning with skeleton cloud colorization.IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(1):509–524, 2023
Reference 75
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Observation babb9b42-5912-4f8a-b345-19005b16bd1e · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Barlow twins: Self- supervised learning via redundancy reduction
Reference 76
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Observation a005fdfd-3faa-4adb-bd71-c8d867257f48 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? S4L: Self-supervised semi-supervised learning
Reference 77
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Observation 46752f6c-d181-48b6-8e5b-80ec5ffff29e · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Colorful image colorization
Reference 78
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Observation 6f453bf6-9e27-4425-ae54-b5a4ce7f37c9 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Combining self-supervised and supervised learning with noisy labels
Reference 79
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Observation 289fe9be-bd3d-4dc9-be26-5ecf85ed6acf · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? iBOT: Image BERT Pre-Training with Online Tokenizer
Reference 80
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Observation 9c21a95f-2874-4075-b6fa-8eb8c5ac42d7 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? 2|X∩Y| |X|+|Y| .(3)
Reference 81
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Observation e520be53-930b-4b45-b6c6-ddc8cf6de573 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? IoU, also called the Jaccard index, measures the average overlap between predicted masks and the ground truth
Reference 82
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Observation e91f8fbf-3ce5-44ab-b56a-7f1c80006c25 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? P= T P T P+F P.(5) 2.Recall:Also called sensitivity, this metric measures how many of the actual positive cases were correctly identified by the model
Reference 83
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Observation 0adb1e97-1854-4d5e-9e8a-cf823be1a113 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? It is computed as the mean of the Average Precision (AP) overNclasses: mAP= 1 N NX i=1 APi,(7) where APi denotes the AP for class i
Reference 84
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Observation 11652693-e6d4-4df2-9da9-cf9f9f464b16 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? SROCC= 1− 6 Pn i=1 d2 i n(n2 −1) ,(9) whered i is is the difference between the ranks ofy i andˆy
Reference 85
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Observation 8702adf4-eee4-4606-8874-a7b34ee089fc · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? Unresolved cited work
Reference 86
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Observation 43e70c49-9caf-4759-994a-9058b11df072 · outbound
Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training? 22 Table 3: Classification performance of different SSL frameworks on CrisisMMD using 128 ×128 image inputs under the PFT and JT training paradigms with 100% labeled data
Reference 87
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