Özal Yıldırım

Cardiology and Cardiovascular Medicine · 2018–2020

A researcher in the Science corpus: 4 papers; trusts 32 researchers and is trusted by 20 researchers here, as inferred from the citation graph.

Subfields

• Cardiology and Cardiovascular Medicine — 37 citations into it; #31 of 906 by trust here, #399 by citations
• Artificial Intelligence — 33 citations into it
• Cognitive Neuroscience — 33 citations into it; #1,701 of 10,852 by trust here, #5,528 by citations
• Computer Vision and Pattern Recognition — 23 citations into it
• Model Architectures — 10 citations into it
• Signal Processing — 8 citations into it

Whom Özal Yıldırım trusts overall

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

1. Yoshua Bengio
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Yann LeCun
5. Alex Graves
6. J. Urgen Schmidhuber
7. Ilya Sutskever
8. Kaiming He
9. Michael I. Jordan
10. Sepp Hochreiter

Who trusts Özal Yıldırım overall

1. Zahra Ebrahimi
2. Jingshan Huang
3. Georgios Petmezas
4. Dr. Prabira Kumar Sethy
5. Mohammad Loni
6. Taoying Li
7. Binqiang Chen
8. Muhammed Talo
9. T. Ozturk
10. Kostas Haris

Papers from Özal Yıldırım's perspective

Ordered by how strongly the researchers Özal Yıldırım 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. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• A novel wavelet sequence based on deep bidirectional LSTM network model for ECG signal classification (2018) — 742 citations
• Automated detection of COVID-19 cases using deep neural networks with X-ray images (2020) — 2,261 citations
• Classification of myocardial infarction with multi-lead ECG signals and deep CNN (2019) — 435 citations
• Arrhythmia detection using deep convolutional neural network with long duration ECG signals (2018) — 760 citations