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dice_coef

Syntologyentry name in harvested coderead from the graph 2026-09-24

dice_coef appears in the code Syntology harvested for 18 papers, as 17 distinct code bodies found in 23 places (a place is one code body under one paper). At least one of them ran in 10 of the papers; 1 of the code bodies carries a behaviour fingerprint.

What this page is not. Routines are grouped here by the exact string of their function or class name. Nothing asserts that two samples named dice_coef do the same thing, share code, or are comparable; the name is a string, not an identity. Behaviour outputs (what a fingerprinted sample returned on the shared battery) are not in this export and are not shown here; the graph at syntology.ai holds them. "Ran" means executed on a synthesized fixture, not that the code is correct or reproduces a paper.

Samples Syntology

Syntology ran 6 of the 17 distinct code bodies named dice_coef; 11 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
0ran · violated contract
0ran · our draft was wrong
0ran · fixture could not drive it
6ran
11unverified
1fingerprinted

Licence is a property of each copy, so it is counted per place: 7 of the 23 places are pointer only (Syntology does not serve that copy's text). This site shows no code text for any sample; every row below links to the file in its repository where the record names one.

“Ran” means the sample executed on a synthesized input; it does not mean the output is correct. “Honoured” and “violated” refer to a contract Syntology drafted from the code itself; “our draft was wrong” and “fixture could not drive it” are failures of Syntology's instrument, not of the code, and those samples did run. The ran count above is every status except unverified, the same rule as each paper page.

Papers

18 papers shown of 18, newest first; 23 places in the table. A paper with no recorded date is placed by the month its arXiv id encodes, shown in the Date column as YYYY-MM (from id). One row per place: a paper whose repository defines the name more than once appears more than once, and the same code body held for several papers appears once under each, with the same status. Titles and dates are the archive's archive 2025-07-28 for papers in the archive, and the graph's for 1 papers added by Syntology; 1 papers have no page here and are shown by arXiv id only. Status and fingerprint are Syntology's record of each code body; licence is recorded for each place. The File cell ends with the code body's code_sha256, Syntology's identity for that exact code: an agent fetches the stored sample with Syntology's MCP tool get_code(code_sha256="…") (how to connect); click an identity to copy that call.

PaperDateFileStatus SyntologyLicence
Understanding the Transfer Limits of Vision Foundation Models added by Syntology 2026-01 (from id) pimed/ProViCNet/ProViCNet/util_functions/utils_weighted.py 129077a6905ca1c9 unverified MIT (permissive)
Pyramid Diffusion for Fine 3D Large Scene Generation 20 Nov 2023 Yuheng-SWJTU/pyramid-discrete-diffusion/utils/loss.py 7f089607644b1aa8 ran fingerprinted MIT (permissive)
CATR: Combinatorial-Dependence Audio-Queried Transformer for Audio-Visual Video Segmentation 18 Sep 2023 aspirinone/catr.github.io/CATR/matcher.py 050cda61d2798c04 ran no licence file found · pointer only
Self-Prompting Large Vision Models for Few-Shot Medical Image Segmentation 15 Aug 2023 peteryyzhang/few-shot-self-prompt-sam/utils/utils.py 45eaa68ef8aa8826 ran no licence file found · pointer only
AdaptiveSAM: Towards Efficient Tuning of SAM for Surgical Scene Segmentation 7 Aug 2023 jayparanjape/biastuning/utils.py 2574ceb4f4225b04 ran no licence file found · pointer only
Spectrum-guided Multi-granularity Referring Video Object Segmentation 25 Jul 2023 bo-miao/sgmg/models/matcher.py 6296ea80154ae7f9 ran licence not identified · pointer only
Diffusion Probabilistic Models for Scene-Scale 3D Categorical Data 2 Jan 2023 zoomin-lee/scene-scale-diffusion/utils/loss.py 7f089607644b1aa8 ran fingerprinted MIT (permissive)
UNeXt: MLP-based Rapid Medical Image Segmentation Network 9 Mar 2022 jeya-maria-jose/unext-pytorch/metrics.py fc0365a30b108850 unverified MIT (permissive)
3D Segmentation with Fully Trainable Gabor Kernels and Pearson's Correlation Coefficient 10 Jan 2022 ibm/multimodal-3d-image-segmentation/nets/custom_losses.py c0f7dcb15e62da45 unverified Apache-2.0 (permissive)
3D Segmentation with Fully Trainable Gabor Kernels and Pearson's Correlation Coefficient 10 Jan 2022 ibm/multimodal-3d-image-segmentation/tensorflow/nets/custom_losses.py a28ccf455345f250 unverified Apache-2.0 (permissive)
Language as Queries for Referring Video Object Segmentation 3 Jan 2022 wjn922/ReferFormer/models/matcher.py 6296ea80154ae7f9 ran Apache-2.0 recorded; this copy not marked cleared · pointer only
Next Day Wildfire Spread: A Machine Learning Data Set to Predict Wildfire Spreading from Remote-Sensing Data 4 Dec 2021 satellitevu/satellitevu-aws-disaster-response-hackathon/deep_learning/metrics.py eabf975a0dc6af2f unverified Apache-2.0 (permissive)
End-to-End Referring Video Object Segmentation with Multimodal Transformers 29 Nov 2021 mttr2021/MTTR/models/matcher.py 6ad1c9eb01d6414b unverified Apache-2.0 (permissive)
Video Instance Segmentation using Inter-Frame Communication Transformers 7 Jun 2021 sukjunhwang/IFC/projects/IFC/ifc/models/segmentation.py 6296ea80154ae7f9 ran Apache-2.0 (permissive)
PraNet: Parallel Reverse Attention Network for Polyp Segmentation 13 Jun 2020 Thehunk1206/PRANet-Polyps-Segmentation/utils/segmentation_metric.py 9552f127ab03fa34 unverified MIT (permissive)
Inf-Net: Automatic COVID-19 Lung Infection Segmentation from CT Images 22 Apr 2020 narges-sa/COVID-CT-Segmentation/main_TV_Unet_Split1.py ee2c6737a0eca8e7 unverified Apache-2.0 (permissive)
UNet++: A Nested U-Net Architecture for Medical Image Segmentation 18 Jul 2018 4uiiurz1/pytorch-nested-unet/metrics.py fc0365a30b108850 unverified MIT (permissive)
UNet++: A Nested U-Net Architecture for Medical Image Segmentation 18 Jul 2018 CarryHJR/Nested-UNet/model.py f2cfef7bbdbe32a7 unverified MIT (permissive)
UNet++: A Nested U-Net Architecture for Medical Image Segmentation 18 Jul 2018 ShawFromAttock/FYP-Medical-Image-Segmentation-using-Nested-UNet-Architecture/metrics.py 6715b71d51fb26e1 unverified MIT (permissive)
U-Net: Convolutional Networks for Biomedical Image Segmentation 18 May 2015 tanyanair/segmentation_uncertainty/bunet/models/bunet.py de7b88d9eb1975c6 ran MIT (permissive)
U-Net: Convolutional Networks for Biomedical Image Segmentation 18 May 2015 mrvturan96/Brain-Tumor-Detection-and-Segmentation-using-Deep-Learning/U-Net/model.py 66eae124c0971826 unverified no licence file found · pointer only
U-Net: Convolutional Networks for Biomedical Image Segmentation 18 May 2015 oliverz17/Unet_Keras/Segmentation_Unet.py eabf975a0dc6af2f unverified no licence file found · pointer only
arXiv:aaai_28465 OpenGVLab/MUTR/models/matcher.py 6296ea80154ae7f9 ran MIT (permissive)

This site shows no code text; each File cell links to the file on GitHub at the repository's current default branch, which may have changed since the harvest. "Pointer only" means Syntology does not serve that copy's text, for one of four reasons: no licence file was found; the licence was not identified; the licence is recorded as permissive but that copy's record is not marked cleared; or the licence is outside the permissive list Syntology serves text under (MIT, Apache-2.0, BSD and similar). Some licences outside that list permit redistribution, such as WTFPL, and GPL-3.0 under its conditions; they are simply not on the list. Hover a licence cell for the reason. Per-sample records for a paper are on its paper page under "Code Syntology ran".

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