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Models/MULAN

MULAN

Reported on 6 benchmarks across 6 tasks · 2 papers · 5 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Methodology5 results

3DonDeepLesion
Sensitivity· 2019-08-12
85.22
best: 88.55 (P3D)
SOTA
MULAN: Multitask Universal Lesion Analysis Network for Joint Lesion Detection, Tagging, and Segmentation arXiv:1908.04373
2D ClassificationonDeepLesion
Sensitivity· 2019-08-12
85.22
best: 88.55 (P3D)
SOTA
MULAN: Multitask Universal Lesion Analysis Network for Joint Lesion Detection, Tagging, and Segmentation arXiv:1908.04373
2D Object DetectiononDeepLesion
Sensitivity· 2019-08-12
85.22
best: 88.55 (P3D)
SOTA
MULAN: Multitask Universal Lesion Analysis Network for Joint Lesion Detection, Tagging, and Segmentation arXiv:1908.04373
16konDeepLesion
Sensitivity· 2019-08-12
85.22
best: 88.55 (P3D)
SOTA
MULAN: Multitask Universal Lesion Analysis Network for Joint Lesion Detection, Tagging, and Segmentation arXiv:1908.04373
Density EstimationonCIFAR-10
NLL (bits/dim)· 2023-12-20
2.55
best: 2.42 (i-DODE)
Diffusion Models With Learned Adaptive Noise arXiv:2312.13236

Computer Vision1 result

Object DetectiononDeepLesion
Sensitivity· 2019-08-12
85.22
best: 88.55 (P3D)
SOTA
MULAN: Multitask Universal Lesion Analysis Network for Joint Lesion Detection, Tagging, and Segmentation arXiv:1908.04373