Argitalpenak (11) ARNE SCHMIDT argitalpenak

2024

  1. An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection

    Expert Systems with Applications, Vol. 240

  2. Focused active learning for histopathological image classification

    Medical Image Analysis, Vol. 95

  3. Introducing instance label correlation in multiple instance learning. Application to cancer detection on histopathological images

    Pattern Recognition, Vol. 146

  4. Probabilistic Attention Based on Gaussian Processes for Deep Multiple Instance Learning

    IEEE Transactions on Neural Networks and Learning Systems, Vol. 35, Núm. 8, pp. 10909-10922

  5. The CrowdGleason dataset: Learning the Gleason grade from crowds and experts

    Computer Methods and Programs in Biomedicine, Vol. 257

2023

  1. Probabilistic Modeling of Inter- and Intra-observer Variability in Medical Image Segmentation

    Proceedings of the IEEE International Conference on Computer Vision

2022

  1. Deep Gaussian processes for multiple instance learning: Application to CT intracranial hemorrhage detection

    Computer Methods and Programs in Biomedicine, Vol. 219

  2. Efficient Cancer Classification by Coupling Semi Supervised and Multiple Instance Learning

    IEEE Access, Vol. 10, pp. 9763-9773

  3. Proportion constrained weakly supervised histopathology image classification

    Computers in Biology and Medicine, Vol. 147

  4. The Devil is in the Details: Whole Slide Image Acquisition and Processing for Artifacts Detection, Color Variation, and Data Augmentation: A Review

    IEEE Access, Vol. 10, pp. 58821-58844

2021

  1. Combining Attention-Based Multiple Instance Learning and Gaussian Processes for CT Hemorrhage Detection

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)