Joon Kyung Kim

Computer Vision and Pattern Recognition · 2016–2020

A researcher in the Science corpus: 3 papers; trusts 12 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 90 citations into it
• Electrical and Electronic Engineering — 65 citations into it

Whom Joon Kyung Kim trusts overall

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

1. Alex Krizhevsky
2. Kaiming He
3. Geoffrey E. Hinton
4. Yu-hsin Chen
5. Christian Szegedy
6. Yann LeCun

Papers from Joon Kyung Kim's perspective

Ordered by how strongly the researchers Joon Kyung Kim 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. Long Short-Term Memory
4. Going deeper with convolutions
5. Learning Multiple Layers of Features from Tiny Images
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. ImageNet Large Scale Visual Recognition Challenge
9. Caffe: Convolutional Architecture for Fast Feature Embedding
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Bit Fusion: Bit-Level Dynamically Composable Architecture for Accelerating Deep Neural Network (2017) — 561 citations
• From high-level deep neural models to FPGAs (2016) — 500 citations
• Planaria: Dynamic Architecture Fission for Spatial Multi-Tenant Acceleration of Deep Neural Networks (2020) — 143 citations