mlsanityData to 7 Oct 2026

Cost-Effective Active Learning for Melanoma Segmentation

arXiv 1711.09168 ↗First posted 24 Nov 2017cs.CVcited by 40

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Abstract (arXiv)

We propose a novel Active Learning framework capable to train effectively a convolutional neural network for semantic segmentation of medical imaging, with a limited amount of training labeled data. Our contribution is a practical Cost-Effective Active Learning approach using dropout at test time as Monte Carlo sampling to model the pixel-wise uncertainty and to analyze the image information to improve the training performance. The source code of this project is available at https://marc-gorriz.github.io/CEAL-Medical-Image-Segmentation/ .

Key facts. Cited by 40 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 Nov 2017.

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Citing papers per year: 2021: 9; 2022: 11; 2023: 10; 2024: 8; 2025: 2.

40 papers.

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  1. 2023A comprehensive survey on deep active learning in medical image analysiscited by 32
  2. 2021All you need are a few pixels: semantic segmentation with PixelPickcited by 30
  3. 2021DSAL: Deeply Supervised Active Learning from Strong and Weak Labelers for Biomedical Image Segmentationcited by 27
  4. 2021Interpretability-Driven Sample Selection Using Self Supervised Learning For Disease Classification And Segmentationcited by 22
  5. 2021Boosting Active Learning via Improving Test Performancecited by 19
  6. 2022LiDAL: Inter-frame Uncertainty Based Active Learning for 3D LiDAR Semantic Segmentationcited by 16
  7. 2022Deep Active Learning with Noise Stabilitycited by 13
  8. 2023Towards Free Data Selection with General-Purpose Modelscited by 10
  9. 2022Patient Aware Active Learning for Fine-Grained OCT Classificationcited by 9
  10. 2024Breaking the Barrier: Selective Uncertainty-based Active Learning for Medical Image Segmentationcited by 9
  11. 2022Self-supervised Assisted Active Learning for Skin Lesion Segmentationcited by 7
  12. 2022Less Is More: A Comparison of Active Learning Strategies for 3D Medical Image Segmentationcited by 7
28 more
  1. 2022Deep Active Learning for Computer Vision: Past and Futurecited by 7
  2. 2021Reducing Annotating Load: Active Learning with Synthetic Images in Surgical Instrument Segmentationcited by 6
  3. 2021CPRAL: Collaborative Panoptic-Regional Active Learning for Semantic Segmentationcited by 6
  4. 2021Towards General and Efficient Active Learningcited by 6
  5. 2024A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentationcited by 6
  6. 2023Deep Active Learning in the Presence of Label Noise: A Surveycited by 5
  7. 2023USIM-DAL: Uncertainty-aware Statistical Image Modeling-based Dense Active Learning for Super-resolutioncited by 4
  8. 2023MoBYv2AL: Self-supervised Active Learning for Image Classificationcited by 3
  9. 2024Predictive Accuracy-Based Active Learning for Medical Image Segmentationcited by 3
  10. 2024Deep Bayesian Active Learning-to-Rank with Relative Annotation for Estimation of Ulcerative Colitis Severitycited by 3
  11. 2021Region-level Active Detector Learningcited by 2
  12. 2022An Active and Contrastive Learning Framework for Fine-Grained Off-Road Semantic Segmentationcited by 2
  13. 2022Knowing What to Label for Few Shot Microscopy Image Cell Segmentationcited by 2
  14. 2023Active Learning for Video Classification with Frame Level Queriescited by 2
  15. 2023EdgeAL: An Edge Estimation Based Active Learning Approach for OCT Segmentationcited by 2
  16. 2024Deep Active Learning with Manifold-preserving Trajectory Samplingcited by 2
  17. 2024GCI-ViTAL: Gradual Confidence Improvement with Vision Transformers for Active Learning on Label Noisecited by 2
  18. 2025Integrating Semi-Supervised and Active Learning for Semantic Segmentationcited by 2
  19. 2021Robust Segmentation Models using an Uncertainty Slice Sampling Based Annotation Workflowcited by 1
  20. 2022Accelerating the creation of instance segmentation training sets through bounding box annotationcited by 1
  21. 2022Semantic Segmentation for Fully Automated Macrofouling Analysis on Coatings after Field Exposurecited by 1
  22. 2023Uncertainty Estimation in Instance Segmentation with Star-convex Shapescited by 1
  23. 2022Deep Active Learning Using Barlow Twinscited by 0
  24. 2023Maturity-Aware Active Learning for Semantic Segmentation with Hierarchically-Adaptive Sample Assessmentcited by 0
  25. 2023MyriadAL: Active Few Shot Learning for Histopathologycited by 0
  26. 2024Active Generation Network of Human Skeleton for Action Recognitioncited by 0
  27. 2024Modular Deep Active Learning Framework for Image Annotation: A Technical Report for the Ophthalmo-AI Projectcited by 0
  28. 2025Boosting Active Learning with Knowledge Transfercited by 0