| Opportunities and obstacles for deep learning in biology and medicine T Ching, DS Himmelstein, BK Beaulieu-Jones, AA Kalinin, BT Do, ... Journal of the royal society interface 15 (141), 20170387, 2018 | 2125 | 2018 |
| Connectomic reconstruction of the inner plexiform layer in the mouse retina M Helmstaedter, KL Briggman, SC Turaga, V Jain, HS Seung, W Denk Nature 500 (7461), 168-174, 2013 | 1157 | 2013 |
| Space–time wiring specificity supports direction selectivity in the retina JS Kim, MJ Greene, A Zlateski, K Lee, M Richardson, SC Turaga, ... Nature 509 (7500), 331-336, 2014 | 534 | 2014 |
| Convolutional networks can learn to generate affinity graphs for image segmentation SC Turaga, JF Murray, V Jain, F Roth, M Helmstaedter, K Briggman, ... Neural computation 22 (2), 511-538, 2010 | 501 | 2010 |
| In toto imaging and reconstruction of post-implantation mouse development at the single-cell level K McDole, L Guignard, F Amat, A Berger, G Malandain, LA Royer, ... Cell 175 (3), 859-876. e33, 2018 | 429 | 2018 |
| Crowdsourcing the creation of image segmentation algorithms for connectomics I Arganda-Carreras, SC Turaga, DR Berger, D Cireşan, A Giusti, ... Frontiers in neuroanatomy 9, 152591, 2015 | 378 | 2015 |
| Mapping social behavior-induced brain activation at cellular resolution in the mouse Y Kim, KU Venkataraju, K Pradhan, C Mende, J Taranda, SC Turaga, ... Cell reports 10 (2), 292-305, 2015 | 324 | 2015 |
| Supervised learning of image restoration with convolutional networks V Jain, JF Murray, F Roth, S Turaga, V Zhigulin, KL Briggman, ... Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on, 1-8, 2007 | 290 | 2007 |
| Large scale image segmentation with structured loss based deep learning for connectome reconstruction J Funke, F Tschopp, W Grisaitis, A Sheridan, C Singh, S Saalfeld, ... IEEE transactions on pattern analysis and machine intelligence 41 (7), 1669-1680, 2018 | 239* | 2018 |
| Machines that learn to segment images: a crucial technology for connectomics V Jain, HS Seung, SC Turaga Current opinion in neurobiology 20 (5), 653-666, 2010 | 184 | 2010 |
| Deep learning enables fast and dense single-molecule localization with high accuracy A Speiser, LR Müller, P Hoess, U Matti, CJ Obara, WR Legant, A Kreshuk, ... Nature methods 18 (9), 1082-1090, 2021 | 175 | 2021 |
| Maximin affinity learning of image segmentation SC Turaga, KL Briggman, M Helmstaedter, W Denk, HS Seung NIPS, 1865-1873, 2009 | 160* | 2009 |
| Behavioral state coding by molecularly defined paraventricular hypothalamic cell type ensembles S Xu, H Yang, V Menon, AL Lemire, L Wang, FE Henry, SC Turaga, ... Science 370 (6514), eabb2494, 2020 | 132 | 2020 |
| Community-based benchmarking improves spike rate inference from two-photon calcium imaging data P Berens, J Freeman, T Deneux, N Chenkov, T McColgan, A Speiser, ... PLoS computational biology 14 (5), e1006157, 2018 | 132 | 2018 |
| Automatic detection of synaptic partners in a whole-brain Drosophila electron microscopy data set J Buhmann, A Sheridan, C Malin-Mayor, P Schlegel, S Gerhard, ... Nature Methods 18 (7), 771-774, 2021 | 128 | 2021 |
| Development of high-throughput, high-resolution 3D reconstruction of large-volume biological tissue using automated tape collection ultramicrotomy and scanning electron microscopy R Schalek, N Kasthuri, K Hayworth, D Berger, J Tapia, J Morgan, ... Microscopy and Microanalysis 17 (S2), 966-967, 2011 | 97 | 2011 |
| Method and apparatus for image processing HS Seung, JF Murray, V Jain, SC Turaga, M Helmstaedter, W Denk US Patent 9,799,098, 2017 | 94 | 2017 |
| Learning to Agglomerate Superpixel Hierarchies V Jain, SC Turaga, KL Briggman, MN Helmstaedter, W Denk, HS Seung Neural Information Processing Systems, 2011 | 83 | 2011 |
| Efficient convolutional neural networks for pixelwise classification on heterogeneous hardware systems F Tschopp, JNP Martel, SC Turaga, M Cook, J Funke 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI), 1225-1228, 2016 | 66 | 2016 |
| Fast amortized inference of neural activity from calcium imaging data with variational autoencoders A Speiser, J Yan, EW Archer, L Buesing, SC Turaga, JH Macke Advances in neural information processing systems 30, 2017 | 60 | 2017 |
H Sebastian SeungProfessor, Princeton Neuroscience Institute and Computer Science Dept.Verified email at princeton.edu
