Hongji Huang
Electrical and Electronic Engineering · 2018–2019
A researcher in the Science corpus: 4 papers; trusts 17 researchers and is trusted by 6 researchers here, as inferred from the citation graph.
Subfields
- Electrical and Electronic Engineering — 29 citations into it; #6,980 of 16,539 by trust here, #7,062 by citations
- Artificial Intelligence — 22 citations into it
- Computer Networks and Communications — 20 citations into it
- Signal Processing — 10 citations into it
- Aerospace Engineering — 7 citations into it
- Building and Construction — 6 citations into it
Whom Hongji Huang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Zubair Muhammad Fadlullah
- Yann LeCun
- Omar El Ayach
- Marc'Aurelio Ranzato
- Nei Kato
- Tim O'Shea
- Fengxiao Tang
- Guan Gui
- Yoshua Bengio
Who trusts Hongji Huang overall
- Fatima Hussain
- Guan Gui
- Mahmoud A. M. Albreem
- Manuel Eugenio Morocho-Cayamcela
- Song Guo
- Hengtao He
- Nguyen Cong Luong
- Syed Ali Hassan
- Mojtaba Vaezi
- Nei Kato
Papers from Hongji Huang's perspective
Ordered by how strongly the researchers Hongji Huang trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Gradient-based learning applied to document recognition
- 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)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet Large Scale Visual Recognition Challenge
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Deep Learning for Super-Resolution Channel Estimation and DOA Estimation Based Massive MIMO System (2018) — 727 citations
- Deep Learning for an Effective Nonorthogonal Multiple Access Scheme (2018) — 453 citations
- Deep-Learning-Based Millimeter-Wave Massive MIMO for Hybrid Precoding (2019) — 424 citations
- Deep Learning for Physical-Layer 5G Wireless Techniques: Opportunities, Challenges and Solutions (2019) — 386 citations