Data Augmentation, Labelling, and Imperfections
Springer International Publishing (Verlag)
978-3-031-17026-3 (ISBN)
DALI 2022 accepted 12 papers from the 22 submissions that were reviewed. The papers focus on rigorous study of medical data related to machine learning systems.
Image Synthesis-based Late Stage Cancer Augmentation and Semi-Supervised Segmentation for MRI Rectal Cancer Staging.- DeepEdit: Deep Editable Learning for Interactive Segmentation of 3D Medical Images.- Long-Tailed Classification of Thorax Diseases on Chest X-Ray: A New Benchmark Study.- Lesser of Two Evils Improves Learning in the Context of Cortical Thickness Estimation Models - Choose Wisely.- TAAL: Test-time Augmentation for Active Learning in Medical Image Segmentation.- Disentangling A Single MR Modality.- CTooth+: A Large-scale Dental Cone Beam Computed Tomography Dataset and Benchmark for Tooth Volume Segmentation.- Noisy Label Classification using Label Noise Selection with Test-Time Augmentation Cross-Entropy and NoiseMix Learning.- CSGAN: Synthesis-Aided Brain MRI Segmentation on 6-Month Infants.- A Stratified Cascaded Approach for Brain Tumor Segmentation with the Aid of Multi-modal Synthetic Data.- Efficient Medical Image Assessment via Self-supervised Learning.- Few-ShotLearning Geometric Ensemble for Multi-label Classification of Chest X-rays.
Erscheinungsdatum | 24.09.2022 |
---|---|
Reihe/Serie | Lecture Notes in Computer Science |
Zusatzinfo | X, 124 p. 45 illus., 43 illus. in color. |
Verlagsort | Cham |
Sprache | englisch |
Maße | 155 x 235 mm |
Gewicht | 218 g |
Themenwelt | Informatik ► Grafik / Design ► Digitale Bildverarbeitung |
Schlagworte | Applications • Artificial Intelligence • Bioinformatics • color image processing • color images • Computer Science • Computer systems • computer vision • conference proceedings • Deep learning • Digital image • Image Analysis • image matching • Image Processing • Image Quality • Image Segmentation • Informatics • machine learning • Medical Images • Neural networks • pattern recognition • reference image • Research • segmentation methods |
ISBN-10 | 3-031-17026-1 / 3031170261 |
ISBN-13 | 978-3-031-17026-3 / 9783031170263 |
Zustand | Neuware |
Haben Sie eine Frage zum Produkt? |
aus dem Bereich