Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels | Paper Citation Record

Observation b2a47423-db0d-4780-add1-bafa77766ec0 · outbound

This paper cites A Review of Particle Shape Effects on Material Properties for Various Engineering Applications: From Macro to Nanoscale,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels A Review of Particle Shape Effects on Material Properties for Various Engineering Applications: From Macro to Nanoscale,

Reference 1

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This paper cites Soil behaviour: The role of particle shape,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Soil behaviour: The role of particle shape,

Reference 2

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Observation a43c88d3-6fd6-4262-9e9f-d907703406b8 · outbound

This paper cites Deep convolutional neural network for 3D mineral identification and liberation analysis,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Deep convolutional neural network for 3D mineral identification and liberation analysis,

Reference 3

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This paper cites Techniques in helical scanning, dynamic imaging and image segmentation for improved quantitative analysis with X-ray micro-CT,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Techniques in helical scanning, dynamic imaging and image segmentation for improved quantitative analysis with X-ray micro-CT,

Reference 4

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This paper cites 3D image segmentation for analysis of multisize particles in a packed particle bed,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels 3D image segmentation for analysis of multisize particles in a packed particle bed,

Reference 5

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Observation 1d358c50-bc23-4ccd-93b3-d7447ea0fbdb · outbound

This paper cites Improved 3d image segmentation for x-ray tomographic analysis of packed particle beds,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Improved 3d image segmentation for x-ray tomographic analysis of packed particle beds,

Reference 6

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Observation 5788c6fe-d861-45a9-99b7-9d6f4f9c130c · outbound

This paper cites Uncertainty-aware particle segmentation for electron microscopy at varied length scales,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Uncertainty-aware particle segmentation for electron microscopy at varied length scales,

Reference 7

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Observation 4d05f3cf-59b1-4640-9906-4e59fab99bb9 · outbound

This paper cites A method of blasted rock image segmentation based on improved watershed algorithm,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels A method of blasted rock image segmentation based on improved watershed algorithm,

Reference 8

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Observation 63c2731d-0a26-42d4-9b61-7ec39ba072c7 · outbound

This paper cites Improved particle separation, characterisation and analysis for ore beneficiation studies using 3d x-ray micro-computed tomography,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Improved particle separation, characterisation and analysis for ore beneficiation studies using 3d x-ray micro-computed tomography,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:27.017687Z

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Observation 474463fb-8e96-41df-b576-ab9ca8fcae65 · outbound

This paper cites Particleseg3d: A scalable out-of-the-box deep learning segmentation solution for individual particle characterization from micro ct images in mineral processing and recycling,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Particleseg3d: A scalable out-of-the-box deep learning segmentation solution for individual particle characterization from micro ct images in mineral processing and recycling,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:26.992324Z

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Observation e6fb30ca-1e1b-4941-99b5-37e86d1e5b50 · outbound

This paper cites Cell detection and segmentation in microscopy images with improved mask r-cnn,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Cell detection and segmentation in microscopy images with improved mask r-cnn,

Reference 11

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Observation d70e8dfe-fa23-44bb-8167-669df16ef2fb · outbound

This paper cites Segment Anything for Microscopy,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Segment Anything for Microscopy,

Reference 12

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Observation 5ad27c01-ab2e-494f-9a40-5eecb27edc13 · outbound

This paper cites Synthetic particle pack generation for augmentation and testing in geological tomographic segmentation,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Synthetic particle pack generation for augmentation and testing in geological tomographic segmentation,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:26.929739Z

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Observation d5157811-8b10-4dc4-b3eb-10b2a684ae2c · outbound

This paper cites Is learning the n-th thing any easier than learning the first?.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Is learning the n-th thing any easier than learning the first?

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:26.905901Z

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Observation dae78588-6167-483d-9ffc-9517fac2e300 · outbound

This paper cites Segment Anything.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Segment Anything

Reference 15

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Observation 7e1d8769-d6a3-442d-b21f-f82f8039b22e · outbound

This paper cites Mask R-CNN.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Mask R-CNN

Reference 16

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Observation eb5f0ca6-521b-4fa0-b6db-a2098e457b70 · outbound

This paper cites Detectron2,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Detectron2,

Reference 17

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This paper cites Ultralytics yolov8,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Ultralytics yolov8,

Reference 18

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Observation a4ca66c0-992a-45d0-bbca-f1e7b5c4f3af · outbound

This paper cites BioImage Model Zoo: A Community-Driven Resource for Accessible Deep Learning in BioImage Analysis,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels BioImage Model Zoo: A Community-Driven Resource for Accessible Deep Learning in BioImage Analysis,

Reference 19

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Observation 02d33e14-6df2-4940-adcb-56bcb24d41a9 · outbound

This paper cites DeepImageJ: A user-friendly environment to run deep learning models in ImageJ,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels DeepImageJ: A user-friendly environment to run deep learning models in ImageJ,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:26.856972Z

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Observation 89ceaa1d-71a1-4662-abe2-659287f52f2f · outbound

This paper cites ilastik: interactive machine learning for (bio)image analysis,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels ilastik: interactive machine learning for (bio)image analysis,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:26.837449Z

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This paper cites Segment anything in medical images,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Segment anything in medical images,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:26.814992Z

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Observation b8364952-e37b-4249-98ee-e95e1b942839 · outbound

This paper cites A survey on self-supervised learning: Algorithms, applications, and future trends,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels A survey on self-supervised learning: Algorithms, applications, and future trends,

Reference 23

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Observation 78e4e9d6-2350-40e0-a3a2-536441e0805f · outbound

This paper cites Masked au- toencoders are scalable vision learners,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Masked au- toencoders are scalable vision learners,

Reference 24

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Observation 7e7f374b-be01-45f8-9b39-fbcbe31b6e95 · outbound

This paper cites Unsupervised Representation Learning by Predicting Image Rotations.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Unsupervised Representation Learning by Predicting Image Rotations

Reference 25

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This paper cites Unsupervised Learning of Visual Representations by Solving Jigsaw Puzzles.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Unsupervised Learning of Visual Representations by Solving Jigsaw Puzzles

Reference 26

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Observation 5e0593d8-fae9-45ff-afbd-ad6628dc6d60 · outbound

This paper cites Contrastive learning of global and local features for medical image segmentation with limited annotations.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Contrastive learning of global and local features for medical image segmentation with limited annotations

Reference 27

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Observation 6fa3bce9-4cb7-4667-a47e-ca4a5a661e64 · outbound

This paper cites Pseudo-label : The simple and efficient semi-supervised learning method for deep neural networks,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Pseudo-label : The simple and efficient semi-supervised learning method for deep neural networks,

Reference 28

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This paper cites Self-training: A survey,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Self-training: A survey,

Reference 29

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This paper cites S4L: Self-Supervised Semi-Supervised Learning,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels S4L: Self-Supervised Semi-Supervised Learning,

Reference 30

Resolution: verified exact; raw_fallback, observed 2026-08-05T17:30:21.558670Z

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Observation a2818b4a-aa4e-4c48-866b-494b79e0ba9f · outbound

This paper cites Semi-supervised learning (chapelle, o. et al., eds.; 2006) [book reviews],.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Semi-supervised learning (chapelle, o. et al., eds.; 2006) [book reviews],

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:26.703908Z

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Observation 44485d60-5efb-4a26-8d23-97bfef0c85ba · outbound

This paper cites Introducing Biomedisa as an open-source online platform for biomedical image segmentation,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Introducing Biomedisa as an open-source online platform for biomedical image segmentation,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:26.683772Z

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This paper cites A Computational Approach to Edge Detection,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels A Computational Approach to Edge Detection,

Reference 33

Resolution: verified exact; raw_fallback, observed 2026-08-05T17:30:21.236476Z

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Observation 3289a564-01ba-483b-b0a5-83a6b3876b61 · outbound

This paper cites Trainable Weka Segmentation: a machine learning tool for microscopy pixel classification,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Trainable Weka Segmentation: a machine learning tool for microscopy pixel classification,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:26.662346Z

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Observation e7288ec5-ee37-4448-a7fc-df6979b38d4c · outbound

This paper cites Fiji: an open-source platform for biological-image analysis,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Fiji: an open-source platform for biological-image analysis,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:26.639925Z

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Observation 42452c91-ebc9-406d-b63b-09c76be78543 · outbound

This paper cites U-Net: Convolutional Networks for Biomedical Image Segmentation,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels U-Net: Convolutional Networks for Biomedical Image Segmentation,

Reference 36

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Observation c4a6ab89-8020-41a6-8e40-b5c1676a0a74 · outbound

This paper cites Accurate and versatile 3D segmentation of plant tissues at cellular resolution,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Accurate and versatile 3D segmentation of plant tissues at cellular resolution,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:26.619432Z

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Observation e878fa6c-816b-4437-a5ef-fe47448ca062 · outbound

This paper cites Deep Watershed Transform for Instance Segmentation,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Deep Watershed Transform for Instance Segmentation,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:26.594237Z

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Observation 4595b905-3bef-4e23-b738-ecaecb203333 · outbound

This paper cites Cellpose: a generalist algorithm for cellular segmentation,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Cellpose: a generalist algorithm for cellular segmentation,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:26.574849Z

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Observation 1635bf61-adee-4583-8847-2380e72ae499 · outbound

This paper cites Microsoft COCO: Common Objects in Context.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Microsoft COCO: Common Objects in Context

Reference 40

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Observation 9e4a0246-076f-432e-816b-ea4cef13ec24 · outbound

This paper cites Imagenet: A large-scale hierarchical image database,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Imagenet: A large-scale hierarchical image database,

Reference 41

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This paper cites You Only Look Once: Unified, Real-Time Object Detection.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels You Only Look Once: Unified, Real-Time Object Detection

Reference 42

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Observation 72ef10b2-7936-49ef-9b60-c43d41833342 · outbound

This paper cites A FORMAL PROOF OF THE KEPLER CONJECTURE,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels A FORMAL PROOF OF THE KEPLER CONJECTURE,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:26.539520Z

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Observation 06021a5f-03ab-40c9-a94b-a3ebfef45792 · outbound

This paper cites A quantified study of segmentation techniques on synthetic geological XRM and FIB-SEM images,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels A quantified study of segmentation techniques on synthetic geological XRM and FIB-SEM images,

Reference 44

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correction dated 2018-09-21. Source: crossref record 10.1007/s10596-018-9780-2->10.1007/s10596-018-9768-y:correction, observed 2026-07-11T03:00:36.656083+00:00. This notice travels one citation hop only.

Observation 944e61e3-7939-4f1e-a254-748957da2111 · outbound

This paper cites Particle classification of iron ore sinter green bed mixtures by 3d x- ray microcomputed tomography and machine learning,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Particle classification of iron ore sinter green bed mixtures by 3d x- ray microcomputed tomography and machine learning,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:26.517376Z

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Observation f44e0a24-e01c-4cc3-8eec-1598d462d06e · outbound

This paper cites Ore image segmentation method using U-Net and Res unet convolutional networks,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Ore image segmentation method using U-Net and Res unet convolutional networks,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:26.501217Z

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Observation d31f1531-2ec6-42dd-9a0d-881930b3344b · outbound

This paper cites Multidimensional characterization of particle morphology and mineralogical composition using ct data and r- vine copulas,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Multidimensional characterization of particle morphology and mineralogical composition using ct data and r- vine copulas,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:26.484648Z

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Observation 4aba843b-8b86-49ac-bc18-e92898fb76c3 · outbound

This paper cites nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:26.465255Z

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Observation d4ee29a4-79d4-44b9-9ac9-5fa34dc84232 · outbound

This paper cites Unsupervised word sense disambiguation rivaling supervised methods,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Unsupervised word sense disambiguation rivaling supervised methods,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:26.443599Z

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Observation 4c3c4ccc-32e2-4da0-918d-f6b8df9a62ae · outbound

This paper cites Text Classification from Labeled and Unlabeled Documents using EM,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Text Classification from Labeled and Unlabeled Documents using EM,

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-05T17:30:16.407229Z

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Observation 9349cf11-c5c1-4bc2-813b-37ff5f4d43b1 · outbound

This paper cites Self-training with noisy student improves imagenet classification,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Self-training with noisy student improves imagenet classification,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:26.292353Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 10cee63b-a291-4b56-ac19-139dca4494f3 · outbound

This paper cites Rethinking pre-training and self-training,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Rethinking pre-training and self-training,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:26.128444Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4aa09a85-442c-4c01-80d2-6f224345cc20 · outbound

This paper cites Unsupervised data augmentation for consistency training,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Unsupervised data augmentation for consistency training,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:25.972465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4c35fb4c-bad2-45b4-9438-38c564e57ffd · outbound

This paper cites Self-training for end-to-end speech recognition,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Self-training for end-to-end speech recognition,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:25.927083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4e47e6f2-2285-4c66-b21f-4a7cc484f289 · outbound

This paper cites Semi- supervised learning for network-based cardiac mr image segmentation,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Semi- supervised learning for network-based cardiac mr image segmentation,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:25.785579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 89d5cf6d-fc19-4743-b833-292f02f8c1c3 · outbound

This paper cites Local contrastive loss with pseudo-label based self-training for semi-supervised medical image segmentation,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Local contrastive loss with pseudo-label based self-training for semi-supervised medical image segmentation,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:25.652831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 18ad6d0e-1790-4b0a-b23b-6ab6d09e5927 · outbound

This paper cites Uncertainty-aware self-training for few-shot text classification,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Uncertainty-aware self-training for few-shot text classification,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:25.425279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 9c28bfb1-0742-44db-b9c6-b682c32f3591 · outbound

This paper cites Anatomically-aware uncertainty for semi-supervised image segmentation,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Anatomically-aware uncertainty for semi-supervised image segmentation,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:25.210064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a2100eb6-d49b-4724-b7bd-40a4d201b077 · outbound

This paper cites Fixmatch: simplifying semi- supervised learning with consistency and confidence,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Fixmatch: simplifying semi- supervised learning with consistency and confidence,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:24.988758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ccd1cc0d-fcc9-47dc-b97a-8c7bf47dd961 · outbound

This paper cites Flexmatch: boosting semi-supervised learning with curriculum pseudo labeling,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Flexmatch: boosting semi-supervised learning with curriculum pseudo labeling,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:24.801226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 88c3b638-e90a-45b3-94c9-fbffe2d7cd29 · outbound

This paper cites Curriculum label- ing: Revisiting pseudo-labeling for semi-supervised learning,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Curriculum label- ing: Revisiting pseudo-labeling for semi-supervised learning,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:24.579325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation abff04bd-99b2-4ab6-8b50-465568f8db81 · outbound

This paper cites NeTra: A toolbox for navigating large image databases,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels NeTra: A toolbox for navigating large image databases,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:24.322973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5275bed7-a13f-4ebe-9cea-c461490ecfef · outbound

This paper cites PyCUDA and PyOpenCL: A scripting-based approach to GPU run-time code generation,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels PyCUDA and PyOpenCL: A scripting-based approach to GPU run-time code generation,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:24.051107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bd77e977-ac9d-43c5-ac6f-dd83b6f9be3a · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels SAM 2: Segment Anything in Images and Videos

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-05T17:30:17.518734Z

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Observation 24b30985-d9d0-41eb-86c6-024ce159c774 · outbound

This paper cites A systematic study of the class imbalance problem in convolutional neural networks,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels A systematic study of the class imbalance problem in convolutional neural networks,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:23.881624Z

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Observation 4cc60645-07cc-44a5-a40d-ee5550b840a1 · outbound

This paper cites An FFT-based technique for translation, rotation, and scale-invariant image registration,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels An FFT-based technique for translation, rotation, and scale-invariant image registration,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:23.641240Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a9d78b96-0c24-42a8-8cb0-147d27ce3d52 · outbound

This paper cites nnInteractive: Redefining 3D Promptable Segmentation.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels nnInteractive: Redefining 3D Promptable Segmentation

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-05T17:30:17.745197Z

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Observation 0357bff2-2ee2-46a2-a03e-94dba1c95168 · outbound

This paper cites Techniques in high-speed imaging and X-ray micro-computed tomography for characterisation of iron ore fragmentation.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Techniques in high-speed imaging and X-ray micro-computed tomography for characterisation of iron ore fragmentation

Reference 68

Resolution: verified exact; local_arxiv, observed 2026-08-05T17:30:20.360733Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bc8a3c75-bfce-4eb1-ae0a-ae03c3e2f27b · outbound

This paper cites Space-filling x-ray source trajectories for efficient scanning in large-angle cone-beam computed tomography,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Space-filling x-ray source trajectories for efficient scanning in large-angle cone-beam computed tomography,

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:23.377093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d08f9e91-02af-4dda-bdeb-46b8abc7f168 · outbound

This paper cites PyTorch: an imperative style, high- performance deep learning library,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels PyTorch: an imperative style, high- performance deep learning library,

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:23.209928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4d99721a-7e73-404c-a745-63c9fc41903e · outbound

This paper cites Is sam 2 better than sam in medical image segmentation?.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Is sam 2 better than sam in medical image segmentation?

Reference 71

Resolution: verified exact; doi, observed 2026-08-05T17:30:19.400999Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f18d41b8-c3a2-4597-8ace-3b4e7679e137 · outbound

This paper cites Chollet et al., “Keras,” https://keras.io, 2015.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Chollet et al., “Keras,” https://keras.io, 2015

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-05T17:30:18.181054Z

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Observation d4c9bb37-20e3-4add-acc2-304ed655934e · outbound

This paper cites TensorFlow: a system for large-scale machine learning,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels TensorFlow: a system for large-scale machine learning,

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:22.992475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bbf04403-7d31-4393-8fdd-b16544637aec · outbound

This paper cites 3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels 3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-05T17:30:18.355047Z

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Observation 73d0934c-0736-4c1f-93fb-88341f959e46 · outbound

This paper cites Natural variability in bee brain size and symmetry revealed by micro-CT imaging and deep learning,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Natural variability in bee brain size and symmetry revealed by micro-CT imaging and deep learning,

Reference 75

Resolution: verified exact; doi, observed 2026-08-05T17:30:19.261638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 70fab330-ffd5-4886-94cc-23e7f0699f37 · outbound

This paper cites Automated 3D cytoplasm segmentation in soft X-ray tomography,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Automated 3D cytoplasm segmentation in soft X-ray tomography,

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:22.804652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 91545fa2-8fa9-474b-88ea-35991d0b16c9 · outbound

This paper cites HEDI: First- Time Clinical Application and Results of a Biomechanical Evaluation and Visualisation Tool for Incisional Hernia Repair,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels HEDI: First- Time Clinical Application and Results of a Biomechanical Evaluation and Visualisation Tool for Incisional Hernia Repair,

Reference 77

Resolution: verified exact; raw_fallback, observed 2026-08-05T17:30:20.074364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 92c5971d-2e46-4b64-a0e5-6cb5d32464e3 · outbound

This paper cites Synchrotron-based 3D X-ray computed tomography reveals root system architecture: Plastic responses to phosphorus placement,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Synchrotron-based 3D X-ray computed tomography reveals root system architecture: Plastic responses to phosphorus placement,

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:22.618903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ad4aa614-0ab3-4cdb-897f-713666ff8bc9 · outbound

This paper cites High-throughput phenomics of global ant biodiversity,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels High-throughput phenomics of global ant biodiversity,

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:22.429777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 53d9bd47-7e77-48f7-bc33-1cfffb46b027 · outbound

This paper cites 3D Slicer: A Platform for Subject-Specific Image Analysis, Visualization, and Clinical Support,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels 3D Slicer: A Platform for Subject-Specific Image Analysis, Visualization, and Clinical Support,

Reference 80

Resolution: verified exact; doi, observed 2026-08-05T17:30:19.143013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ad212e6c-36be-44b6-8c0f-7b7681c9b2a7 · outbound

This paper cites Matplotlib: A 2d graphics environment,.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Matplotlib: A 2d graphics environment,

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:30:22.232369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1bc5f13c-5736-46f5-b6ee-6390db8454ae · outbound

This paper cites Available: http://ieeexplore.ieee.org/document/8099788/.

Self-Validated Learning for Particle Separation: A Correctness-Based Self-Training Framework Without Human Labels Available: http://ieeexplore.ieee.org/document/8099788/

Reference 2866

Resolution: verified exact; raw_fallback, observed 2026-08-05T17:30:20.865347Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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