Andreas Fischbach
Plant Science · 2009–2017
A researcher in the Science corpus: 6 papers; trusts 110 researchers and is trusted by 13 researchers here, as inferred from the citation graph.
Subfields
- Plant Science — 70 citations into it; #4,066 of 8,232 by trust here, #2,616 by citations
- Computer Vision and Pattern Recognition — 65 citations into it; #8,714 of 21,575 by trust here, #11,286 by citations
- Computational Biology & Bioinformatics — 26 citations into it
- Artificial Intelligence — 19 citations into it; #26,499 of 35,345 by trust here, #30,347 by citations
- Molecular Biology — 14 citations into it
- Computational Theory and Mathematics — 12 citations into it; #9,140 of 12,182 by trust here, #9,306 by citations
- Ecology — 11 citations into it; #5,527 of 10,717 by trust here, #7,168 by citations
- Environmental Engineering — 11 citations into it; #3,024 of 5,479 by trust here, #2,867 by citations
Whom Andreas Fischbach trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Massimo Minervini
- Victor S. Lempitsky
- Sotirios A. Tsaftaris
- David G. Lowe
- Jean-Michel Pape
- Hanno Scharr
- Andrew Zisserman
- Xuming He
- Matthias Heiler
- Claudia Nieuwenhuis
Who trusts Andreas Fischbach overall
- Massimo Minervini
- Mengye Ren
- Hanno Scharr
- Jean-Michel Pape
- Jordan R. Ubbens
- Jörg Stork
- Mario Valerio Giuffrida
- Christian Klukas
Papers from Andreas Fischbach's perspective
Ordered by how strongly the researchers Andreas Fischbach trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet: A large-scale hierarchical image database
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Distinctive Image Features from Scale-Invariant Keypoints
- Gradient-based learning applied to document recognition
- ImageNet Large Scale Visual Recognition Challenge
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
Their papers
- Finely-grained annotated datasets for image-based plant phenotyping (2016) — 306 citations
- Annotated Image Datasets of Rosette Plants (2014) — 101 citations
- Efficient global optimization for combinatorial problems (2014) — 62 citations
- Simultaneous phenotyping of leaf growth and chlorophyll fluorescence via GROWSCREEN FLUORO allows detection of stress tolerance in Arabidopsis thaliana and other rosette plants. (2009) — 292 citations
- Surrogate-Assisted Learning of Neural Networks (2017) — 7 citations
- GROWSCREEN-Rhizo is a novel phenotyping robot enabling simultaneous measurements of root and shoot growth for plants grown in soil-filled rhizotrons. (2012) — 331 citations