Athina P. Petropulu
Electrical and Electronic Engineering · 2006–2021
A researcher in the Science corpus: 13 papers; trusts 71 researchers and is trusted by 20 researchers here, as inferred from the citation graph.
Subfields
- Electrical and Electronic Engineering — 117 citations into it; #8,690 of 16,539 by trust here, #6,973 by citations
- Aerospace Engineering — 99 citations into it; #1,008 of 6,421 by trust here, #954 by citations
- Computer Networks and Communications — 66 citations into it; #3,694 of 9,886 by trust here, #2,613 by citations
- Signal Processing — 42 citations into it
- Computational Mechanics — 29 citations into it; #6,030 of 10,001 by trust here, #5,350 by citations
- Biomedical Engineering — 25 citations into it
- Artificial Intelligence — 19 citations into it
- Computer Vision and Pattern Recognition — 13 citations into it
Whom Athina P. Petropulu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- E.J. Candes
- Chun-Yang Chen
- Jian Li
- P. Stoica
- Hirotugu Akaike
- Claude E. Shannon
- Rui Zhang
- David Tse
- Terence Tao
- Yann LeCun
Who trusts Athina P. Petropulu overall
- Fan Liu
- Christos Masouros
- Kaitao Meng
- Gan Zheng
- H. Hua
- Nanchi Su
- Jie Xu
- Qingqing Wu
- Weijie Yuan
- Zhiqiang Xiao
Papers from Athina P. Petropulu's perspective
Ordered by how strongly the researchers Athina P. Petropulu trusts endorse each paper. Same corpus, a different order for every researcher.
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- Understanding the difficulty of training deep feedforward neural networks
Their papers
- Improving Physical Layer Secrecy Using Full-Duplex Jamming Receivers (2013) — 367 citations
- Improving Wireless Physical Layer Security via Cooperating Relays (2010) — 1,362 citations
- A Deep Learning Framework for Optimization of MISO Downlink Beamforming (2019) — 313 citations
- Towards Multi-Functional 6G Wireless Networks: Integrating Sensing, Communication and Security (2021) — 423 citations
- On Cooperative Relaying Schemes for Wireless Physical Layer Security (2010) — 409 citations
- An Overview of Signal Processing Techniques for Joint Communication and Radar Sensing (2021) — 1,156 citations
- MIMO Radar for Advanced Driver-Assistance Systems and Autonomous Driving: Advantages and Challenges (2020) — 586 citations
- Joint Radar and Communication Design: Applications, State-of-the-Art, and the Road Ahead (2019) — 1,850 citations
- Toward Dual-functional Radar-Communication Systems: Optimal Waveform Design (2017) — 925 citations
- Optimum Co-Design for Spectrum Sharing between Matrix Completion Based MIMO Radars and a MIMO Communication System (2015) — 349 citations
- Power Allocation Strategies for Target Localization in Distributed Multiple-Radar Architectures (2011) — 324 citations
- MIMO Radar Using Compressive Sampling (2009) — 309 citations
- 14 FROM LINEAR ADAPTIVE FILTERING TO NONLINEAR INFORMATION PROCESSING (2006) — 34 citations