Carlos Busso
Experimental and Cognitive Psychology · 2004–2019
A researcher in the Science corpus: 9 papers; trusts 33 researchers and is trusted by 22 researchers here, as inferred from the citation graph.
Subfields
- Experimental and Cognitive Psychology — 57 citations into it; #1,977 of 9,731 by trust here, #730 by citations
- Artificial Intelligence — 56 citations into it; #11,413 of 35,345 by trust here, #5,924 by citations
- Signal Processing — 34 citations into it; #3,481 of 7,572 by trust here, #1,147 by citations
- Social Psychology — 25 citations into it; #6,747 of 15,694 by trust here, #2,360 by citations
- Cognitive Neuroscience — 21 citations into it
- Computer Vision and Pattern Recognition — 15 citations into it
- Evaluation & Benchmarks — 8 citations into it
- Statistics and Probability — 5 citations into it
Whom Carlos Busso trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Michael Grimm
- Björn Schuller
- Paul A. Taylor
- R. Cowie
- Klaus R. Scherer
- C. Burges
- Shrikanth S. Narayanan
- Kristian Kroschel
- Florian Eyben
- Chi-Chun Lee
Who trusts Carlos Busso overall
- Soujanya Poria
- Jinming Zhao
- Navonil Majumder
- Reza Lotfian
- Amir Zadeh
- Devamanyu Hazarika
- Rui Liu
- Leonardo Pepino
- Shrikanth S. Narayanan
- Percy Liang
Papers from Carlos Busso's perspective
Ordered by how strongly the researchers Carlos Busso trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- The Vera am Mittag German audio-visual emotional speech database (IEEE International Conference on Multimedia and Expo)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- The Nature of Statistical Learning Theory
- Gradient-based learning applied to document recognition
- Emotional speech: Towards a new generation of databases (Speech Communication)
- Attention is All you Need (Neural Information Processing Systems)
Their papers
- Analysis of emotion recognition using facial expressions, speech and multimodal information (2004) — 952 citations
- IEMOCAP: interactive emotional dyadic motion capture database (2008) — 4,482 citations
- Building Naturalistic Emotionally Balanced Speech Corpus by Retrieving Emotional Speech from Existing Podcast Recordings (2019) — 467 citations
- MSP-IMPROV: An Acted Corpus of Dyadic Interactions to Study Emotion Perception (2017) — 401 citations
- Driver Modeling for Detection and Assessment of Driver Distraction: Examples from the UTDrive Test Bed (2017) — 57 citations
- The ordinal nature of emotions (2017) — 106 citations
- The Geneva Minimalistic Acoustic Parameter Set (GeMAPS) for Voice Research and Affective Computing (2016) — 1,837 citations
- Emotion recognition using a hierarchical binary decision tree approach (2011) — 452 citations
- Analysis of Emotionally Salient Aspects of Fundamental Frequency for Emotion Detection (2009) — 303 citations