Moritz Helmstaedter

Computer Vision and Pattern Recognition · 2007–2018

A researcher in the Science corpus: 9 papers; trusts 104 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 53 citations into it; #14,461 of 21,575 by trust here, #7,249 by citations
• Cellular and Molecular Neuroscience — 37 citations into it; #1,674 of 2,998 by trust here, #455 by citations
• Cognitive Neuroscience — 32 citations into it
• Biophysics — 27 citations into it
• Neuroscience — 19 citations into it
• Structural Biology — 19 citations into it
• Molecular Biology — 18 citations into it; #9,545 of 17,773 by trust here, #5,914 by citations
• Surfaces, Coatings and Films — 14 citations into it

Whom Moritz Helmstaedter trusts overall

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

1. Kevin L. Briggman
2. J. White
3. Davi D. Bock
4. Viren Jain
5. Christoph Sommer
6. Srinivas C. Turaga
7. Albert Cardona
8. Winfried Denk
9. John C. Fiala
10. Yann LeCun

Who trusts Moritz Helmstaedter overall

1. Richard F. Betzel
2. Guangyu Robert Yang
3. D. Bassett
4. Wenlu Zhang
5. Shilin Qiu
6. Viren Jain
7. José Ignacio Orlando
8. Olaf Sporns
9. Naveed Akhtar
10. Xiao-Jing Wang

Papers from Moritz Helmstaedter's perspective

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

1. Gradient-based learning applied to document recognition
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. ImageNet classification with deep convolutional neural networks
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. ImageNet Large Scale Visual Recognition Challenge
6. ImageNet: A large-scale hierarchical image database
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
9. Backpropagation Applied to Handwritten Zip Code Recognition
10. Distinctive Image Features from Scale-Invariant Keypoints

Their papers

• Supervised Learning of Image Restoration with Convolutional Networks (2007) — 253 citations
• Maximin affinity learning of image segmentation (2009) — 150 citations
• Boundary Learning by Optimization with Topological Constraints (2010) — 155 citations
• Cellular-resolution connectomics: challenges of dense neural circuit reconstruction (2013) — 307 citations
• Connectomic reconstruction of the inner plexiform layer in the mouse retina (2013) — 981 citations
• Wiring specificity in the direction-selectivity circuit of the retina (2011) — 833 citations
• Dense connectomic reconstruction in layer 4 of the somatosensory cortex (2018) — 308 citations
• Convolutional Networks Can Learn to Generate Affinity Graphs for Image Segmentation (2010) — 408 citations
• Petilla terminology: nomenclature of features of GABAergic interneurons of the cerebral cortex (2008) — 1,516 citations