Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-11T22:27:31.323706Z
Paper Citation Record · LEDGER
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation
As of 20 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 0 inbound Pith citation observations for arXiv:2412.03458.
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.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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
Reference resolution
58 of 58 outbound references displayed
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External citation measurements
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Outbound references
Observation 675f9abd-4a09-4818-b6ff-9efd9162071a · outbound
This paper cites & Others Deep learning for automatic segmentation of thigh and leg muscles.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation & Others Deep learning for automatic segmentation of thigh and leg muscles
Reference 1
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Observation 72cbe109-0760-4ee7-abd0-45e2503d303d · outbound
This paper cites Recent advances in o pin- ion modeling: control and social influence.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation Recent advances in o pin- ion modeling: control and social influence
Reference 2
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Observation ea86a229-1bfe-497f-8013-f0abb67d33f4 · outbound
This paper cites On the optimal control of opinion dy- namics on evolving networks.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation On the optimal control of opinion dy- namics on evolving networks
Reference 3
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Observation 885ca824-3d0a-4685-80fe-eb1b2807cb51 · outbound
This paper cites On the equivalence between Fourier-based and Wasserstein metric s.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation On the equivalence between Fourier-based and Wasserstein metric s
Reference 4
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Observation 25e34b4e-be9c-4501-93f1-700296c8a79e · outbound
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Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation & Tanno, R
Reference 5
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Observation 47c4e6bd-9bca-4c36-b600-bc330883a7d5 · outbound
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Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation & Cox, D
Reference 6
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Observation d708423b-b370-4cdd-a1a4-1e65cf708f81 · outbound
This paper cites Optimizing the Dice Score and Jaccard Index for Medical Image Segmentation: Theory & Practice.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation Optimizing the Dice Score and Jaccard Index for Medical Image Segmentation: Theory & Practice
Reference 7
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Observation 213256af-24ad-4090-92d4-64554fe1f50c · outbound
This paper cites & Lorenzi, T.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation & Lorenzi, T
Reference 8
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Observation 781bd9a0-fee6-4b8e-9a40-2cc4becb4ff6 · outbound
This paper cites & Zanella, M.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation & Zanella, M
Reference 9
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Observation 59dbc752-8855-47b3-bf41-8b24ff9ab960 · outbound
This paper cites A., Fornasier, M., Rosado, J.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation A., Fornasier, M., Rosado, J
Reference 10
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Observation a4365817-2d0b-42f3-b608-0aff1535ace1 · outbound
This paper cites A., Fornasier, M., Toscani, G., and Vecil, F.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation A., Fornasier, M., Toscani, G., and Vecil, F
Reference 11
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Observation d13c8aa4-d391-4776-901d-7ac003e3545d · outbound
This paper cites & Loreto, V.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation & Loreto, V
Reference 12
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Observation da33d8f7-ea54-4e37-a858-89b0dfcc145e · outbound
This paper cites MUC-4 evaluation metrics.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation MUC-4 evaluation metrics
Reference 13
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Observation 2ba4a547-148f-4686-92b1-6fe386a3f581 · outbound
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Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation & Ayache, N
Reference 14
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Observation c53a304e-772e-476f-93a0-462db46c7011 · outbound
This paper cites & Collins, D.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation & Collins, D
Reference 15
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Source-reported events for the cited work
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Observation c7fe0e37-b133-4e6c-8afd-b50bd2eb9131 · outbound
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Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation & Weisbuch, G
Reference 16
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Observation 4a1d912a-e4a6-4115-936a-8bc321d8a209 · outbound
This paper cites Reaching a consensus.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation Reaching a consensus
Reference 17
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Observation 13f161bf-70ae-4406-ad17-cd8831c21291 · outbound
This paper cites Measures of the Amount of Ecologic Association Betwee n Species.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation Measures of the Amount of Ecologic Association Betwee n Species
Reference 18
- Resolution
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Source-reported events for the cited work
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Observation 92d152f3-8e93-4c98-9f9f-e4663c6048d8 · outbound
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Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation & Pareschi, L
Reference 19
- Resolution
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Source-reported events for the cited work
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Observation d969f521-fcb1-493a-be49-c4d258d14cc2 · outbound
This paper cites Opinion dynamics: inhomogeneous Boltzmann-type equations modelling opinion leadership and political se - gregation.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation Opinion dynamics: inhomogeneous Boltzmann-type equations modelling opinion leadership and political se - gregation
Reference 20
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Observation 65763a5d-5719-43ee-8d8b-39294d6da5a4 · outbound
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Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation Opinion formation systems via deterministic particles approximation
Reference 21
- Resolution
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Source-reported events for the cited work
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Observation bcc7057c-49bf-4873-a883-b3fc2e40baf5 · outbound
This paper cites A formal theory of social power.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation A formal theory of social power
Reference 22
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Observation 2108547b-b2d0-4eb6-9b96-907d10ada921 · outbound
This paper cites Opinion formation on evolving network: the DP A method applied to a nonlocal cross-diffusion PDE-ODE system.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation Opinion formation on evolving network: the DP A method applied to a nonlocal cross-diffusion PDE-ODE system
Reference 23
- Resolution
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Source-reported events for the cited work
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Observation c0163073-425f-4f66-9e8a-dd957273f74b · outbound
This paper cites & Krishnapuram, R.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation & Krishnapuram, R
Reference 24
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Observation b04b697b-37b9-4351-a1f7-1c6070eade5a · outbound
This paper cites Opinion dynamics and bounded confi dence models, analysis, and simulation.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation Opinion dynamics and bounded confi dence models, analysis, and simulation
Reference 25
- Resolution
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Source-reported events for the cited work
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Observation ddfab658-e6ed-4e06-9015-412307cfd403 · outbound
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Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation & Visconti, G
Reference 26
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Observation 29580fad-cd09-4193-8f80-050e41c4ac5a · outbound
This paper cites Deep learning techniqu es for medical image segmentation: achievements and challenges.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation Deep learning techniqu es for medical image segmentation: achievements and challenges
Reference 27
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Observation 30d74903-b6d4-40f4-bfaf-e2782b6ff266 · outbound
This paper cites nnU-Net: a self-configuring method for deep learning-based biomedical image s egment- ation.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation nnU-Net: a self-configuring method for deep learning-based biomedical image s egment- ation
Reference 28
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Observation 9e8119e0-49be-4619-b308-78798ed3186e · outbound
This paper cites The distribution of the flora in the alpine zone.1.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation The distribution of the flora in the alpine zone.1
Reference 29
- Resolution
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Observation fd960ef7-1ac1-4529-aff3-f07c597e44e6 · outbound
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Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation Data clustering: a review
Reference 30
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Observation a8ed41cf-628a-4bdf-a7a1-f22c002e346b · outbound
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Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation Unsupervised image segmentation using the Deffuant- Weisbuch model from social dynamics
Reference 31
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Observation 70f0f66b-e27e-45d1-8290-377b85035b7f · outbound
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Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation Uncertainty quantification us ing Bayesian neural networks in classification: application to biomedical image segmentation
Reference 32
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Observation d8144c5b-023c-46e3-972a-0793ccab9294 · outbound
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Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation A review of deep-learning-ba sed medical image segmentation methods
Reference 33
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Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation Quantification of pulmonary involvement in COVID-19 pneumonia by means of a cascade of two U-nets: training and asses sment on multiple datasets using different annotation criteria
Reference 34
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Observation d26b85fe-008f-4882-8f58-35cab30832d2 · outbound
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Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation Quantification of pulmonary involvement in COVID-19 pneumonia: an upgrade of the LungQuant software fo r lung CT segmentation
Reference 35
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Observation 2267a66c-d051-49aa-8197-41c209591b0a · outbound
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Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation Uncertainty quantification and control of kinetic models of tumour growth under clinical uncertain ties
Reference 36
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Observation b3b2b55a-d1ac-4a68-9ab5-fd4638adf9cc · outbound
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Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation A comprehensive survey of image segmentation: clustering meth ods, performance parameters, and benchmark datasets
Reference 37
- Resolution
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Observation 8aa5a009-5f4c-4dc6-9949-9f78af195c32 · outbound
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Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation Heterophilious dynamics enhances con sensus
Reference 38
- Resolution
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Source-reported events for the cited work
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Observation 3c642a65-d815-4f7d-a757-e103d48b1aba · outbound
This paper cites Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy
Reference 39
- Resolution
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Source-reported events for the cited work
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Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation Steering opinion dynamics through control of social networks
Reference 40
- Resolution
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Observation 0980b034-49ba-4656-9cfe-43dead43cd8c · outbound
This paper cites An Introduction to Monte Carlo Metho ds for the Boltzmann Equation.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation An Introduction to Monte Carlo Metho ds for the Boltzmann Equation
Reference 41
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 218a2215-b89b-4ab0-9650-76c87e522441 · outbound
This paper cites Interacting multiagent systems: kin etic equa- tions and Monte Carlo msethods.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation Interacting multiagent systems: kin etic equa- tions and Monte Carlo msethods
Reference 42
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 42a8ee47-33ce-4dca-bee6-ff9e6494c241 · outbound
This paper cites Hydrodynamic mo dels of preference formation in multi-agent societies.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation Hydrodynamic mo dels of preference formation in multi-agent societies
Reference 43
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation e3ac9839-28af-4db8-b1fa-c7538a26ddbe · outbound
This paper cites & Zanella, M.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation & Zanella, M
Reference 44
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation ebbc9e8c-bde6-4800-bd1a-3138fb587640 · outbound
This paper cites Model-based assessment of the impact of driver-assist vehicles using kinetic theory.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation Model-based assessment of the impact of driver-assist vehicles using kinetic theory
Reference 45
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation c8d40841-53ba-41f7-88a7-b0c2b9d44c72 · outbound
This paper cites A trainable clustering algo rithm based on shortest paths from density peaks.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation A trainable clustering algo rithm based on shortest paths from density peaks
Reference 46
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation baa4f408-3daa-4f49-ba7c-776076216190 · outbound
This paper cites A Bayesian Approach to Clustering via the Proper Bayesian Bootstrap: the Bayesian Bagged Clustering (BBC) algorithm.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation A Bayesian Approach to Clustering via the Proper Bayesian Bootstrap: the Bayesian Bagged Clustering (BBC) algorithm
Reference 47
- Resolution
- verified exact
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation cc0a5479-53c3-4fb7-837c-54d23794f977 · outbound
This paper cites Opinion Dynamics and Bounded Confidenc e: Models, Analysis and Simulation.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation Opinion Dynamics and Bounded Confidenc e: Models, Analysis and Simulation
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T22:27:31.577471Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation da919138-a34b-4280-a0bf-4be149480534 · outbound
This paper cites U-net: Convolutional networks for biomedical image segmentation.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation U-net: Convolutional networks for biomedical image segmentation
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T22:27:31.562107Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation c1b465fb-a0e1-4251-99b4-2311babc8211 · outbound
This paper cites The truth of the f-measure.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation The truth of the f-measure
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T22:27:31.546395Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation a4542f41-8fb9-4987-b4ca-1db3f4dc5bbd · outbound
This paper cites & Aggarwal, L.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation & Aggarwal, L
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T22:27:31.531716Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation ba380207-5487-4dd1-8daa-37cf2a14e9ae · outbound
This paper cites & Sznajd, J.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation & Sznajd, J
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T22:27:31.515987Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 117b2cd5-4d7c-4332-8008-030a10f3836d · outbound
This paper cites & Hanbury, A.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation & Hanbury, A
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T22:27:31.498222Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 59282706-1821-486d-ad95-5a35647489d8 · outbound
This paper cites Kinetic models of opinion formation.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation Kinetic models of opinion formation
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T22:27:31.481570Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation e64334da-1cdf-49ce-98e1-a0f4b15d94b7 · outbound
This paper cites an unresolved cited work.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation Unresolved cited work
Reference 55
- Resolution
- unresolved
- raw_fallback, observed 2026-08-11T22:27:31.466540Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation de6b9063-3e0c-471a-8ff1-bbe1976436cf · outbound
This paper cites & Tian, J.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation & Tian, J
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T22:27:31.451691Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation b658aa5a-40ae-4477-a1df-7d1a31280208 · outbound
This paper cites & Liang, J.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation & Liang, J
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T22:27:31.436248Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation d6f9eda3-da2f-4d18-bda1-6ff8fd7c4409 · outbound
This paper cites an unresolved cited work.
Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-based Segmentation Unresolved cited work
Reference 2015
- Resolution
- unresolved
- raw_fallback, observed 2026-08-11T22:27:32.348011Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Pith citing papers
No inbound Pith citation observations are available.