Alexandros Iosifidis

Computer Vision and Pattern Recognition · with Tefas · 2012–2020

A researcher in the Science corpus: 9 papers; trusts 366 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 85 citations into it; #11,027 of 21,575 by trust here, #18,266 by citations
• Artificial Intelligence — 67 citations into it; #16,989 of 35,345 by trust here, #26,682 by citations
• Management Science and Operations Research — 34 citations into it; #4,540 of 11,946 by trust here, #5,316 by citations
• Finance — 28 citations into it; #7,025 of 10,518 by trust here, #8,598 by citations
• Economics and Econometrics — 19 citations into it; #15,346 of 23,481 by trust here, #18,597 by citations
• Model Architectures — 17 citations into it
• Electrical and Electronic Engineering — 11 citations into it
• Optimization & Training — 11 citations into it

Whom Alexandros Iosifidis trusts overall

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

1. Heng Wang
2. G. Huang
3. Ivan Laptev
4. Paul J. Werbos
5. Cordelia Schmid
6. Geoffrey E. Hinton
7. Teuvo Kohonen
8. Diederik P. Kingma
9. Marcin Marszalek
10. Alexander Kläser

Who trusts Alexandros Iosifidis overall

1. Anastasios Tefas
2. Dat Thanh Tran
3. Michalis Vrigkas
4. Nikolaos Passalis
5. Weiwei Jiang
6. Ioannis Pitas
7. Juho Kanniainen
8. Martin Magris
9. A. Ozbayoglu
10. Omer Berat Sezer

Papers from Alexandros Iosifidis's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
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. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Using deep learning to detect price change indications in financial markets (2017) — 145 citations
• Forecasting Stock Prices from the Limit Order Book Using Convolutional Neural Networks (2017) — 329 citations
• Tensor representation in high-frequency financial data for price change prediction (2017) — 63 citations
• Discriminant Bag of Words based representation for human action recognition (2014) — 80 citations
• Deep learning and computer vision will transform entomology (2020) — 382 citations
• Time-series classification using neural Bag-of-Features (2017) — 39 citations
• Benchmark Dataset for Mid-Price Prediction of Limit Order Book data (2017) — 31 citations
• Minimum Variance Extreme Learning Machine for human action recognition (2014) — 34 citations
• View-Invariant Action Recognition Based on Artificial Neural Networks (2012) — 143 citations