Dan Nie

Cognitive Neuroscience · 2011–2014

A researcher in the Science corpus: 2 papers; trusts 10 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Cognitive Neuroscience — 17 citations into it; #4,047 of 10,852 by trust here, #4,616 by citations
• Experimental and Cognitive Psychology — 16 citations into it; #3,333 of 9,731 by trust here, #3,491 by citations
• Artificial Intelligence — 6 citations into it
• Computer Vision and Pattern Recognition — 5 citations into it

Whom Dan Nie trusts overall

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

1. Margaret M. Bradley
2. Mu Li
3. Yuhai Wu
4. Chih-Jen Lin
5. Abdulhamit Subasi
6. Peter J. Lang
7. Bao-Liang Lu
8. M. Murugappan
9. Keith Anderson

Who trusts Dan Nie overall

1. Wei-Long Zheng
2. Soraia M. Alarcão
3. Robert Jenke
4. Bao-Liang Lu
5. Min-Ki Kim
6. Wei Liu
7. Lin Shu
8. Manuel José Fonseca
9. Angelika Peer
10. Miyoung Kim

Papers from Dan Nie's perspective

Ordered by how strongly the researchers Dan Nie trusts endorse each paper. Same corpus, a different order for every researcher.

1. Emotion Assessment: Arousal Evaluation Using EEG's and Peripheral Physiological Signals (Multimedia Content Representation, Classification and Security)
2. LIBSVM: A library for support vector machines
3. EEG signal classification using wavelet feature extraction and a mixture of expert model (Expert systems with applications)
4. A global geometric framework for nonlinear dimensionality reduction.
5. Frontal brain electrical activity (EEG) distinguishes valence and intensity of musical emotions
6. Statistical Learning Theory
7. Modeling naturalistic affective states via facial and vocal expressions recognition (International Conference on Multimodal Interaction)
8. Which Emotions Can be Induced by Music? What Are the Underlying Mechanisms? And How Can We Measure Them?
9. Music and emotion: electrophysiological correlates of the processing of pleasant and unpleasant music. (Psychophysiology)
10. Prosody-based automatic detection of annoyance and frustration in human-computer dialog

Their papers

• Emotional state classification from EEG data using machine learning approach (2014) — 715 citations
• EEG-based emotion recognition during watching movies (2011) — 373 citations