Superpixel powered autoencoder technique for detecting dementia

Author:

Bansal Deepika1,Khanna Kavita1ORCID,Chhikara Rita1,Dua Rakesh Kumar2,Malhotra Rajeev3

Affiliation:

1. Department of Computer Science & Engineering The NorthCap University Gurugram India

2. Department of NeuroSurgery Fortis Hospital New Delhi India

3. Department of NeuroSurgery Max Super Speciality Hospital New Delhi India

Publisher

Wiley

Subject

Artificial Intelligence,Computational Theory and Mathematics,Theoretical Computer Science,Control and Systems Engineering

Reference74 articles.

1. SLIC superpixels compared to state‐of‐the‐art superpixel methods;Achanta R.;IEEE Transactions on Pattern Analysis and Machine Intelligence,2012

2. Voice pathology detection and classification by adopting online sequential extreme learning machine;Al‐Dhief F. T.;IEEE Access,2021

3. Baldi P.(2012 June).Autoencoders unsupervised learning and deep architectures. InProceedings of ICML workshop workshop on unsupervised and transfer learning(pp. 37–49). JMLR Workshop and Conference Proceedings.

4. Comparative analysis of various machine learning algorithms for detecting dementia;Bansal D.;Procedia Computer Science,2018

5. Bansal D. Khanna K. Chhikara R. Dua R. K. &Malhotra R.(2019a October).A study on dementia using machine learning techniques. InCommunication and computing systems: Proceedings of the 2nd international conference on communication and computing systems (ICCCS 2018) December 1–2 2018 Gurgaon India (p. 414). CRC Press.

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