Omer Berat Sezer
Management Science and Operations Research · 2017–2020
A researcher in the Science corpus: 7 papers; trusts 348 researchers and is trusted by 13 researchers here, as inferred from the citation graph.
Subfields
- Management Science and Operations Research — 296 citations into it; #1,903 of 11,946 by trust here, #2,603 by citations
- Artificial Intelligence — 200 citations into it; #21,768 of 35,345 by trust here, #22,463 by citations
- Time-Series & Forecasting — 185 citations into it; #56 of 381 by trust here, #107 by citations
- Economics and Econometrics — 111 citations into it
- Finance — 104 citations into it; #2,586 of 10,518 by trust here, #4,482 by citations
- Economics & Operations Research — 103 citations into it; #155 of 244 by trust here, #171 by citations
- Computer Vision and Pattern Recognition — 83 citations into it; #9,807 of 21,575 by trust here, #16,787 by citations
- Electrical and Electronic Engineering — 81 citations into it; #3,087 of 16,539 by trust here, #9,402 by citations
Whom Omer Berat Sezer trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- A. Ozbayoglu
- Diederik P. Kingma
- J. Urgen Schmidhuber
- Ilya Sutskever
- Yann LeCun
- Alex Krizhevsky
- Christopher Krauss
- Ruslan Salakhutdinov
Who trusts Omer Berat Sezer overall
- A. Ozbayoglu
- Weiwei Jiang
- M. Ugur Gudelek
- Longbing Cao
- Shree Krishna Sharma
- Pedro Lara-Benítez
- Sami ben Jabeur
- Yinheng Li
- Fei Wang
- Mohammed Ali Al-Garadi
Papers from Omer Berat Sezer's perspective
Ordered by how strongly the researchers Omer Berat Sezer 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)
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Algorithmic financial trading with deep convolutional neural networks: Time series to image conversion approach (2018) — 387 citations
- Deep Learning for Financial Applications : A Survey (2020) — 513 citations
- Financial Trading Model with Stock Bar Chart Image Time Series with Deep Convolutional Neural Networks (2019) — 59 citations
- A Deep Neural-Network Based Stock Trading System Based on Evolutionary Optimized Technical Analysis Parameters (2017) — 92 citations
- An Artificial Neural Network-based Stock Trading System Using Technical Analysis and Big Data Framework (2017) — 66 citations
- Financial Time Series Forecasting with Deep Learning : A Systematic Literature Review: 2005-2019 (2019) — 1,431 citations
- Context-Aware Computing, Learning, and Big Data in Internet of Things: A Survey (2018) — 386 citations