Fred A. Hamprecht

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74 articles

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Coauteurs

Anna KreshukGroup Leader, EMBL HeidelbergAdresse e-mail validée de embl.de
Bjoern H MenzeUniversität ZürichAdresse e-mail validée de uzh.ch
Bjoern AndresTU DresdenAdresse e-mail validée de andres.sc
Thorsten BeierQuantStackAdresse e-mail validée de quantstack.net
Christoph-Nikolas StraehleResearch Scientist, Bosch Center for Artificial IntelligenceAdresse e-mail validée de de.bosch.com
Carsten HauboldPhD Student, University of HeidelbergAdresse e-mail validée de iwr.uni-heidelberg.de
Hanno SteenProfessor of Pathology, Harvard Medical SchoolAdresse e-mail validée de childrens.harvard.edu
Martin SchieggResearch Scientist, Bosch Center for AIAdresse e-mail validée de bosch.com
Bernhard RenardHasso Plattner InstituteAdresse e-mail validée de hpi.de
Bernhard X. KauslerAdresse e-mail validée de kausler.net
Judith A. Jebanathirajah SteenAssociate Professor of Neurology, Harvard Medical SchoolAdresse e-mail validée de childrens.harvard.edu
Melih KandemirAssociate Professor of Machine Learning at the University of Southern DenmarkAdresse e-mail validée de imada.sdu.dk
Christoph SommerIST AustriaAdresse e-mail validée de ist.ac.at
Jörg Hendrik KappesHeidelberg EngineeringAdresse e-mail validée de math.uni-heidelberg.de
Graham KnottSenior Scientist, EPFLAdresse e-mail validée de epfl.ch
Michael HanselmannTechnology Owner & Senior Manager (AI, Automated Driving), Robert Bosch GmbHAdresse e-mail validée de de.bosch.com
Adrian WolnyPostdoc, EMBL, HeidelbergAdresse e-mail validée de embl.de
Steffen WolfMRC Laboratory of Molecular Biology, CambridgeAdresse e-mail validée de mrc-lmb.cam.ac.uk
Xinghua Lou, Ph.D.Vicarious AIAdresse e-mail validée de vicarious.com
Ferran DiegoTelefónica ResearchAdresse e-mail validée de telefonica.com

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Fred A. Hamprecht

Professor, Heidelberg University

Adresse e-mail validée de iwr.uni-heidelberg.de - Page d'accueil

Scientific AI Quantum Chemistry Machine Learning


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Ilastik: interactive machine learning for (bio) image analysis S Berg, D Kutra, T Kroeger, CN Straehle, BX Kausler, C Haubold, ... Nature methods 16 (12), 1226-1232, 2019	1823	2019
Development and assessment of new exchange-correlation functionals FA Hamprecht, AJ Cohen, DJ Tozer, NC Handy The Journal of chemical physics 109 (15), 6264-6271, 1998	1766	1998
On the spectral bias of neural networks N Rahaman, A Baratin, D Arpit, F Draxler, M Lin, F Hamprecht, Y Bengio, ... International conference on machine learning, 5301-5310, 2019	1388	2019
Ilastik: Interactive learning and segmentation toolkit C Sommer, C Straehle, U Koethe, FA Hamprecht 2011 IEEE international symposium on biomedical imaging: From nano to macro …, 2011	1381	2011
A comparison of random forest and its Gini importance with standard chemometric methods for the feature selection and classification of spectral data BH Menze, BM Kelm, R Masuch, U Himmelreich, P Bachert, W Petrich, ... BMC bioinformatics 10, 1-16, 2009	1283	2009
An objective comparison of cell-tracking algorithms V Ulman, M Maška, KEG Magnusson, O Ronneberger, C Haubold, ... Nature methods 14 (12), 1141-1152, 2017	595	2017
Essentially no barriers in neural network energy landscape F Draxler, K Veschgini, M Salmhofer, F Hamprecht International conference on machine learning, 1309-1318, 2018	421	2018
Learning steerable filters for rotation equivariant cnns M Weiler, FA Hamprecht, M Storath Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018	417	2018
On oblique random forests BH Menze, BM Kelm, DN Splitthoff, U Koethe, FA Hamprecht Machine Learning and Knowledge Discovery in Databases: European Conference …, 2011	326	2011
Three-dimensional quantitative similarity− activity relationships (3d qsiar) from seal similarity matrices H Kubinyi, FA Hamprecht, T Mietzner Journal of medicinal chemistry 41 (14), 2553-2564, 1998	300	1998
Multi-modal brain tumor segmentation using deep convolutional neural networks G Urban, M Bendszus, F Hamprecht, J Kleesiek MICCAI BraTS (brain tumor segmentation) challenge. Proceedings, winning …, 2014	295	2014
Learning to count with regression forest and structured labels L Fiaschi, U Köthe, R Nair, FA Hamprecht Proceedings of the 21st international conference on pattern recognition …, 2012	271	2012
Robust prediction of the MASCOT score for an improved quality assessment in mass spectrometric proteomics T Koenig, BH Menze, M Kirchner, F Monigatti, KC Parker, T Patterson, ... Journal of proteome research 7 (9), 3708-3717, 2008	250	2008
A comparative study of modern inference techniques for structured discrete energy minimization problems JH Kappes, B Andres, FA Hamprecht, C Schnörr, S Nowozin, D Batra, ... International Journal of Computer Vision 115, 155-184, 2015	241	2015
A comparative study of modern inference techniques for discrete energy minimization problems J Kappes, B Andres, F Hamprecht, C Schnorr, S Nowozin, D Batra, S Kim, ... Proceedings of the IEEE conference on computer vision and pattern …, 2013	222	2013
Visualizing a homogeneous blend in bulk heterojunction polymer solar cells by analytical electron microscopy M Pfannmoller, H Flugge, G Benner, I Wacker, C Sommer, M Hanselmann, ... Nano letters 11 (8), 3099-3107, 2011	214	2011
Accurate and versatile 3D segmentation of plant tissues at cellular resolution A Wolny, L Cerrone, A Vijayan, R Tofanelli, AV Barro, M Louveaux, ... Elife 9, e57613, 2020	206	2020
Imagining the future of bioimage analysis E Meijering, AE Carpenter, H Peng, FA Hamprecht, JC Olivo-Marin Nature biotechnology 34 (12), 1250-1255, 2016	203	2016
Common limitations of image processing metrics: A picture story A Reinke, MD Tizabi, CH Sudre, M Eisenmann, T Rädsch, M Baumgartner, ... arXiv preprint arXiv:2104.05642, 2021	174	2021
Multicut brings automated neurite segmentation closer to human performance T Beier, C Pape, N Rahaman, T Prange, S Berg, DD Bock, A Cardona, ... Nature methods 14 (2), 101-102, 2017	169	2017

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