Volker Steinhage, PD Dr.
Volker Steinhage, PD Dr.
Acad. Dir., Bonn Univ.
Verified email at
Cited by
Cited by
Nonlinear discriminant analysis using kernel functions
V Roth, V Steinhage
Advances in neural information processing systems 12, 1999
LeafNet: A computer vision system for automatic plant species identification
P Barré, BC Stöver, KF Müller, V Steinhage
Ecological Informatics 40, 50-56, 2017
Extracting buildings from aerial images using hierarchical aggregation in 2D and 3D
A Fischer, TH Kolbe, F Lang, AB Cremers, W Förstner, L Plümer, ...
Computer vision and image understanding 72 (2), 185-203, 1998
Identification of Africanized honey bees through wing morphometrics: two fast and efficient procedures
TM Francoy, D Wittmann, M Drauschke, S Müller, V Steinhage, ...
Apidologie 39 (5), 488-494, 2008
Biodiversity informatics in action: identification and monitoring of bee species using ABIS
T Arbuckle, S Schröder, V Steinhage, D Wittmann
Proceedings of the 15th International Symposium Informatics for …, 2001
Performance of histogram descriptors for the classification of 3D laser range data in urban environments
J Behley, V Steinhage, AB Cremers
2012 IEEE international conference on robotics and automation, 4391-4398, 2012
Laser-based segment classification using a mixture of bag-of-words
J Behley, V Steinhage, AB Cremers
2013 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2013
Models for photogrammetric building reconstruction
C Braun, TH Kolbe, F Lang, W Schickler, V Steinhage, AB Cremers, ...
Computers & Graphics 19 (1), 109-118, 1995
Efficient Radius Neighbor Search in Three-dimensional Point Clouds
J Behley, V Steinhage, AB Cremers
IEEE International Conference on Robotics and Automation (ICRA), 2015
Morphometric and genetic changes in a population of Apis mellifera after 34 years of Africanization
TM Francoy, D Wittmann, V Steinhage, M Drauschke, S Müller, DR Cunha, ...
Genet. Mol. Res 8 (2), 709-717, 2009
Identification of animals and recognition of their actions in wildlife videos using deep learning techniques
F Schindler, V Steinhage
Ecological Informatics 61, 101215, 2021
High-precision phenotyping of grape bunch architecture using fast 3D sensor and automation
F Rist, K Herzog, J Mack, R Richter, V Steinhage, R Töpfer
Sensors 18 (3), 763, 2018
Image-based species identification of wild bees using convolutional neural networks
K Buschbacher, D Ahrens, M Espeland, V Steinhage
Ecological Informatics 55, 101017, 2020
Automated 3D reconstruction of grape cluster architecture from sensor data for efficient phenotyping
F Schöler, V Steinhage
Computers and Electronics in Agriculture 114, 163-177, 2015
Towards a multisensor station for automated biodiversity monitoring
JW Wägele, P Bodesheim, SJ Bourlat, J Denzler, M Diepenbroek, ...
Basic and Applied Ecology 59, 105-138, 2022
High-precision 3D detection and reconstruction of grapes from laser range data for efficient phenotyping based on supervised learning
J Mack, C Lenz, J Teutrine, V Steinhage
Computers and Electronics in Agriculture 135, 300-311, 2017
The new key to bees: automated identification by image analysis of wings
S Schroder, D Wittmann, W Drescher, V Roth, V Steinhage, AB Cremers
Pollinating bees–the Conservation Link Between Agriculture and Nature …, 2002
An adaptable approach to automated visual detection of plant organs with applications in grapevine breeding
J Grimm, K Herzog, F Rist, A Kicherer, R Toepfer, V Steinhage
Biosystems Engineering 183, 170-183, 2019
Efficient identification, localization and quantification of grapevine inflorescences and flowers in unprepared field images using Fully Convolutional Networks
R Rudolph, K Herzog, R Töpfer, V Steinhage
Vitis 58 (3), 95-104, 2019
Automated extraction and analysis of morphological features for species identification
V Steinhage, S Schröder, KH Lampe, AB Cremers
Automated object identification in systematics: theory, approaches, and …, 2007
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