Roshan Joy Martis

Cognitive Neuroscience · 2012–2014

A researcher in the Science corpus: 4 papers; trusts 10 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Cognitive Neuroscience — 37 citations into it; #4,822 of 10,852 by trust here, #5,162 by citations
• Cardiology and Cardiovascular Medicine — 27 citations into it; #215 of 906 by trust here, #498 by citations
• Signal Processing — 24 citations into it
• Artificial Intelligence — 15 citations into it
• Pulmonary and Respiratory Medicine — 6 citations into it

Whom Roshan Joy Martis trusts overall

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

1. Charles M. Bishop
2. Paul S. Addison
3. Juan Pablo Martínez
4. Nello Cristianini
5. Simon S. Haykin
6. Hojjat Adeli
7. Samanwoy Ghosh-Dastidar
8. Abdulhamit Subasi
9. Rute Almeida
10. Usha R. Acharya

Who trusts Roshan Joy Martis overall

1. Fatin A. Elhaj
2. Lieven Billiet
3. Naomie Binti Salim
4. Özal Yıldırım
5. S. Van Huffel
6. Arief R. Harris
7. Tan Tian Swee

Papers from Roshan Joy Martis's perspective

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

1. Analysis of EEG records in an epileptic patient using wavelet transform. (Journal of Neuroscience Methods)
2. A neural-network-based detection of epilepsy (Neurological Research)
3. Entropies for detection of epilepsy in EEG (Comput. Methods Programs Biomed.)
4. Artificial Neural Network Based Epileptic Detection Using Time-Domain and Frequency-Domain Features (Journal of medical systems)
5. EEG signal classification using wavelet feature extraction and a mixture of expert model (Expert systems with applications)
6. A wavelet-based ECG delineator: evaluation on standard databases (IEEE Transactions on Biomedical Engineering)
7. Physiological time-series analysis using approximate entropy and sample entropy. (American Journal of Physiology. Heart and Circulatory Physiology)
8. An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods
9. Imaging brain dynamics using independent component analysis (Proceedings of the IEEE)
10. A new supervised learning algorithm for multiple spiking neural networks with application in epilepsy and seizure detection (Neural Networks)

Their papers

• Wavelet-based Machine Learning Techniques for ECG Signal Analysis (2014) — 28 citations
• Automated EEG analysis of epilepsy: A review (2013) — 816 citations
• ECG beat classification using PCA, LDA, ICA and Discrete Wavelet Transform (2013) — 709 citations
• Application of principal component analysis to ECG signals for automated diagnosis of cardiac health (2012) — 300 citations