Andreas Kamilaris

Plant Science · 2017–2019

A researcher in the Science corpus: 4 papers; trusts 238 researchers and is trusted by 21 researchers here, as inferred from the citation graph.

Subfields

• Plant Science — 36 citations into it; #748 of 8,232 by trust here, #2,041 by citations
• Computer Vision and Pattern Recognition — 34 citations into it; #6,909 of 21,575 by trust here, #7,750 by citations
• Artificial Intelligence — 31 citations into it
• Ecology — 27 citations into it; #4,824 of 10,717 by trust here, #6,392 by citations
• Information Systems — 20 citations into it
• Media Technology — 18 citations into it
• Environmental Engineering — 15 citations into it
• Model Architectures — 14 citations into it

Whom Andreas Kamilaris trusts overall

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

1. J. Urgen Schmidhuber
2. Alex Krizhevsky
3. Yann LeCun
4. Geoffrey E. Hinton
5. Feng Tian
6. Yoshua Bengio
7. Karen Simonyan
8. Jia Deng
9. Suchet Bargoti
10. Kentaro Kuwata

Who trusts Andreas Kamilaris overall

1. Samuel C. Hassler
2. Muhammad Hammad Saleem
3. Lili Li
4. Verónica Sáiz-Rubio
5. Dimosthenis C. Tsouros
6. Anand Koirala
7. Rajendra P. Sishodia
8. J. G. Arnal Barbedo
9. Fulya Baysal-Gurel
10. Johan Potgieter

Papers from Andreas Kamilaris's perspective

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

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

Their papers

• The Rise of Blockchain Technology in Agriculture and Food Supply Chains (2019) — 992 citations
• A review of the use of convolutional neural networks in agriculture (2018) — 414 citations
• Deep learning in agriculture: A survey (2018) — 4,300 citations
• A review on the practice of big data analysis in agriculture (2017) — 949 citations