Shantanu Singh
Biophysics · 2016–2019
A researcher in the Science corpus: 9 papers; trusts 57 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Biophysics — 115 citations into it; #733 of 1,196 by trust here, #206 by citations
- Molecular Biology — 90 citations into it; #12,380 of 17,773 by trust here, #6,095 by citations
- Computer Vision and Pattern Recognition — 84 citations into it
- Media Technology — 62 citations into it
- Medical Imaging — 51 citations into it
- Artificial Intelligence — 47 citations into it
- Computational Biology & Bioinformatics — 31 citations into it
- Evaluation & Benchmarks — 21 citations into it
Whom Shantanu Singh trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Anne E Carpenter
- Oren Z. Kraus
- Ron Kohavi
- Thouis Raymond Jones
- Kaiming He
- Christoph Sommer
- Karen Simonyan
- E. Glory
- Christian Szegedy
- Brendan J. Frey
Who trusts Shantanu Singh overall
Papers from Shantanu Singh's perspective
Ordered by how strongly the researchers Shantanu Singh trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- ImageNet Large Scale Visual Recognition Challenge
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Gradient-based learning applied to document recognition
- GENERATIVE ADVERSARIAL NETS
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Rectified Linear Units Improve Restricted Boltzmann Machines
- Long Short-Term Memory
Their papers
- Data-analysis strategies for image-based cell profiling (2017) — 696 citations
- CellProfiler 3.0: Next-generation image processing for biology (2018) — 1,741 citations
- Applications in image-based profiling of perturbations. (2016) — 160 citations
- Nucleus segmentation across imaging experiments: The 2018 Data Science Bowl (2019) — 781 citations
- Cell Painting, a high-content image-based assay for morphological profiling using multiplexed fluorescent dyes (2016) — 960 citations
- Evaluation of Deep Learning Strategies for Nucleus Segmentation in Fluorescence Images (2018) — 308 citations
- CytoGAN: Generative Modeling of Cell Images (2017) — 72 citations
- CP-CHARM: segmentation-free image classification made accessible (2016) — 59 citations
- Automating Morphological Profiling with Generic Deep Convolutional Networks (2016) — 90 citations