Mark H. Michalski

Artificial Intelligence · 2018

A researcher in the Science corpus: 2 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 11 citations into it

Whom Mark H. Michalski trusts

Their strongest outbound trust, strongest first, inferred from their citations.

1. Matthew D. Zeiler (in Artificial Intelligence)

Papers from Mark H. Michalski's perspective

Ordered by how strongly the researchers Mark H. Michalski trusts endorse each paper. Same corpus, a different order for every researcher.

1. U-Net: Convolutional Networks for Biomedical Image Segmentation (International Conference on Medical Image Computing and Computer-Assisted Intervention)
2. Image-to-Image Translation with Conditional Adversarial Networks
3. Aggregated Residual Transformations for Deep Neural Networks
4. V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation
5. ADADELTA: An Adaptive Learning Rate Method
6. Medical Image Synthesis with Context-Aware Generative Adversarial Networks
7. Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
8. The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)
9. Dermatologist-level classification of skin cancer with deep neural networks
10. Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs.

Their papers

• Medical Image Synthesis for Data Augmentation and Anonymization using Generative Adversarial Networks (2018) — 676 citations
• DeepSPINE: Automated Lumbar Vertebral Segmentation, Disc-level Designation, and Spinal Stenosis Grading Using Deep Learning (2018) — 48 citations