Kyle W. Karhohs
Computer Vision and Pattern Recognition · 2012–2019
A researcher in the Science corpus: 4 papers; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 58 citations into it
Whom Kyle W. Karhohs trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Who trusts Kyle W. Karhohs overall
Papers from Kyle W. Karhohs's perspective
Ordered by how strongly the researchers Kyle W. Karhohs trusts endorse each paper. Same corpus, a different order for every researcher.
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Rectified Linear Units Improve Restricted Boltzmann Machines
- ImageNet classification with deep convolutional neural networks
- Fully convolutional networks for semantic segmentation
- This PDF file includes: Materials and Methods
- Mask R-CNN
- U-Net: Convolutional Networks for Biomedical Image Segmentation (International Conference on Medical Image Computing and Computer-Assisted Intervention)
- Human-level control through deep reinforcement learning
- Gradient-based learning applied to document recognition
Their papers
- CellProfiler 3.0: Next-generation image processing for biology (2018) — 1,741 citations
- Nucleus segmentation across imaging experiments: The 2018 Data Science Bowl (2019) — 781 citations
- p53 Dynamics Control Cell Fate (2012) — 742 citations
- Evaluation of Deep Learning Strategies for Nucleus Segmentation in Fluorescence Images (2018) — 308 citations