617 citations · 718 across the 10 of their papers we have counts for
4 papers · 1 filter
Primary Tumor and Inter-Organ Augmentations for Supervised Lymph Node Colon Adenocarcinoma Metastasis Detection
Apostolia Tsirikoglou, Karin Stacke, Gabriel Eilertsen +1
The scarcity of labeled data is a major bottleneck for developing accurate and robust deep learning-based models for histopathology applications. The problem is notably prominent f…
How to cheat with metrics in single-image HDR reconstruction
Gabriel Eilertsen, Saghi Hajisharif, Param Hanji +3
Single-image high dynamic range (SI-HDR) reconstruction has recently emerged as a problem well-suited for deep learning methods. Each successive technique demonstrates an improveme…
Ensembles of GANs for synthetic training data generation
Gabriel Eilertsen, Apostolia Tsirikoglou, Claes Lundström +1
Insufficient training data is a major bottleneck for most deep learning practices, not least in medical imaging where data is difficult to collect and publicly available datasets a…
Unsupervised anomaly detection in digital pathology using GANs
Milda Pocevičiūtė, Gabriel Eilertsen, Claes Lundström
Machine learning (ML) algorithms are optimized for the distribution represented by the training data. For outlier data, they often deliver predictions with equal confidence, even t…