Shiji Song
Computer Vision and Pattern Recognition · 2013–2023
A researcher in the Science corpus: 19 papers; trusts 1,504 researchers and is trusted by 19 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 630 citations into it; #7,082 of 21,575 by trust here, #5,205 by citations
- Artificial Intelligence — 493 citations into it; #18,830 of 35,345 by trust here, #7,945 by citations
- Model Architectures — 258 citations into it
- Efficiency & Compression — 168 citations into it; #1,181 of 1,264 by trust here, #944 by citations
- Optimization & Training — 82 citations into it
- Electrical and Electronic Engineering — 61 citations into it
- Evaluation & Benchmarks — 35 citations into it
- Aerospace Engineering — 32 citations into it
Whom Shiji Song trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Kaiming He
- Geoffrey E. Hinton
- Yoshua Bengio
- Ross B. Girshick
- Diederik P. Kingma
- Yann LeCun
- Ilya Sutskever
- Karen Simonyan
- Christian Szegedy
Who trusts Shiji Song overall
- G. Huang
- Yulin Wang
- Gao Huang
- Xiaodi Li
- Xuran Pan
- Lieven Billiet
- Bowen Pan
- Yizeng Han
- Dongchen Han
- Youwei Liang
Papers from Shiji Song's perspective
Ordered by how strongly the researchers Shiji Song trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Going deeper with convolutions
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- 3D Object Detection with Pointformer (2020) — 460 citations
- Dynamic Neural Networks: A Survey (2021) — 940 citations
- Resolution Adaptive Networks for Efficient Inference (2020) — 247 citations
- Vision Transformer with Deformable Attention (2022) — 822 citations
- Implicit Semantic Data Augmentation for Deep Networks (2019) — 242 citations
- Glance and Focus: a Dynamic Approach to Reducing Spatial Redundancy in Image Classification (2020) — 172 citations
- Not All Images are Worth 16x16 Words: Dynamic Transformers for Efficient Image Recognition (2021) — 264 citations
- Adaptive Focus for Efficient Video Recognition (2021) — 118 citations
- Semi-Supervised and Unsupervised Extreme Learning Machines (2014) — 741 citations
- On the Integration of Self-Attention and Convolution (2021) — 490 citations
- Trends in extreme learning machines: A review (2015) — 1,704 citations
- FLatten Transformer: Vision Transformer using Focused Linear Attention (2023) — 394 citations
- Not All Images are Worth 16x16 Words: Dynamic Vision Transformers with Adaptive Sequence Length (2021) — 48 citations
- Stabilization of Delay Systems: Delay-Dependent Impulsive Control (2017) — 469 citations
- Lagrangian relaxation for the reliable shortest path problem with correlated link travel times (2017) — 56 citations
- A Reduction of the Elastic Net to Support Vector Machines with an Application to GPU Computing (2014) — 46 citations
- Search for narrow resonances using the dijet mass spectrum in pp collisions at √s=8 TeV (2013) — 162 citations
- Search for the standard model Higgs boson produced in association with a W or a Z boson and decaying to bottom quarks (2013) — 232 citations
- Energy calibration and resolution of the CMS electromagnetic calorimeter in pp collisions at √s = 7 TeV (2013) — 188 citations