Konstantinos Drossos

Computer Vision and Pattern Recognition · 2018–2020

A researcher in the Science corpus: 4 papers; trusts 121 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 36 citations into it; #17,612 of 21,575 by trust here, #12,992 by citations
• Artificial Intelligence — 33 citations into it; #28,554 of 35,345 by trust here, #19,018 by citations
• Signal Processing — 24 citations into it; #6,093 of 7,572 by trust here, #3,099 by citations
• Representation & Self-Supervised Learning — 18 citations into it
• Evaluation & Benchmarks — 9 citations into it

Whom Konstantinos Drossos trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Jimmy Ba
4. Yoshua Bengio
5. Karen Simonyan
6. Alex Krizhevsky
7. Andrej Karpathy
8. Andrew Zisserman
9. Frederic Font
10. Kaiming He

Who trusts Konstantinos Drossos overall

1. Benjamin Elizalde
2. Eduardo Fonseca
3. Yusong Wu
4. Andreea-Maria Oncescu
5. Haohe Liu
6. Soham Deshmukh
7. Rongjie Huang
8. Felix Kreuk
9. Dongchao Yang
10. Zesen Cheng

Papers from Konstantinos Drossos's perspective

Ordered by how strongly the researchers Konstantinos Drossos 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. ImageNet: A large-scale hierarchical image database
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Gradient-based learning applied to document recognition
9. ImageNet Large Scale Visual Recognition Challenge
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Clotho: an Audio Captioning Dataset (2019) — 604 citations
• COALA: Co-Aligned Autoencoders for Learning Semantically Enriched Audio Representations (2020) — 35 citations
• VOICe: A Sound Event Detection Dataset For Generalizable Domain Adaptation (2019) — 4 citations
• Unsupervised adversarial domain adaptation for acoustic scene classification (2018) — 46 citations