C. Stringer
Artificial Intelligence · bioRxiv · 2016–2024
A researcher in the Science corpus: 8 papers; trusts 206 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 65 citations into it
- Computer Vision and Pattern Recognition — 63 citations into it
- Biophysics — 50 citations into it; #730 of 1,196 by trust here, #500 by citations
- Media Technology — 26 citations into it; #2,993 of 3,621 by trust here, #1,079 by citations
- Molecular Biology — 23 citations into it; #14,560 of 17,773 by trust here, #12,742 by citations
- Evaluation & Benchmarks — 18 citations into it
- Medical Imaging — 18 citations into it
- Electrical and Electronic Engineering — 11 citations into it
Whom C. Stringer trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Leon A. Gatys
- Kaiming He
- Geoffrey E. Hinton
- Olaf Ronneberger
- Alex Krizhevsky
- Marius Pachitariu
- L. V. D. van der Maaten
- Ilya Loshchilov
- Yoshua Bengio
- X. Zhang
Who trusts C. Stringer overall
- Marius Pachitariu
- N. A. Cayco-Gajic
- Nicholas A. Steinmetz
- Lukas Heumos
- Kristopher T. Jensen
- R. Silver
- Eftychios A. Pnevmatikakis
- Kohei Nakajima
- Johannes Friedrich
- Alessio Ansuini
Papers from C. Stringer's perspective
Ordered by how strongly the researchers C. Stringer 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
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Long Short-Term Memory
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- Cellpose: a generalist algorithm for cellular segmentation (2020) — 3,569 citations
- Cellpose 2.0: how to train your own model (2022) — 1,118 citations
- Spike sorting with Kilosort4 (2024) — 320 citations
- Cellpose3: one-click image restoration for improved cellular segmentation (2024) — 377 citations
- Omnipose: a high-precision morphology-independent solution for bacterial cell segmentation (2021) — 328 citations
- Spontaneous Behaviors Drive Multidimensional, Brain-wide Activity (2019) — 902 citations
- High-dimensional geometry of population responses in visual cortex (2018) — 647 citations
- Suite2p: beyond 10,000 neurons with standard two-photon microscopy (2016) — 1,087 citations