Sung Wook Baik

Computer Vision and Pattern Recognition · 2017–2020

A researcher in the Science corpus: 9 papers; trusts 163 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 69 citations into it; #11,824 of 21,575 by trust here, #9,563 by citations
• Artificial Intelligence — 52 citations into it
• Safety, Risk, Reliability and Quality — 18 citations into it; #468 of 1,220 by trust here, #508 by citations
• Model Architectures — 13 citations into it
• Electrical and Electronic Engineering — 12 citations into it
• Evaluation & Benchmarks — 8 citations into it
• Information Systems — 5 citations into it

Whom Sung Wook Baik trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Yangqing Jia
4. Ilya Sutskever
5. Jia Deng
6. Yoshua Bengio
7. Alex Graves
8. Yann LeCun
9. Ross B. Girshick
10. Kaiming He

Who trusts Sung Wook Baik overall

1. Khan Muhammad

Papers from Sung Wook Baik's perspective

Ordered by how strongly the researchers Sung Wook Baik 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. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. ImageNet Large Scale Visual Recognition Challenge
8. Going deeper with convolutions
9. Attention is All you Need (Neural Information Processing Systems)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Multi-grade brain tumor classification using deep CNN with extensive data augmentation (2019) — 782 citations
• Action Recognition in Video Sequences using Deep Bi-Directional LSTM With CNN Features (2018) — 672 citations
• Efficient Deep CNN-Based Fire Detection and Localization in Video Surveillance Applications (2019) — 428 citations
• Convolutional Neural Networks Based Fire Detection in Surveillance Videos (2018) — 448 citations
• A Novel CNN-GRU-Based Hybrid Approach for Short-Term Residential Load Forecasting (2020) — 430 citations
• Oversampling Techniques for Bankruptcy Prediction: Novel Features from a Transaction Dataset (2018) — 76 citations
• A Cluster-Based Boosting Algorithm for Bankruptcy Prediction in a Highly Imbalanced Dataset (2018) — 79 citations
• Speech Emotion Recognition from Spectrograms with Deep Convolutional Neural Network (2017) — 358 citations
• Early fire detection using convolutional neural networks during surveillance for effective disaster management (2017) — 461 citations