The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Deep Machine Learning - A New Frontier in Artificial Intelligence Research [Research Frontier]
Abstract
This article provides an overview of the mainstream deep learning approaches and research directions proposed over the past decade. It is important to emphasize that each approach has strengths and "weaknesses, depending on the application and context in "which it is being used. Thus, this article presents a summary on the current state of the deep machine learning field and some perspective into how it may evolve. Convolutional Neural Networks (CNNs) and Deep Belief Networks (DBNs) (and their respective variations) are focused on primarily because they are well established in the deep learning field and show great promise for future work.
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Metadata
- Authors
- Arel, I., Rose, D. C., & Karnowski, T. P.
- Venue
- IEEE Computational Intelligence Magazine
- Published
- 2010-11
- Volume
- 5
- Issue
- 4
- Pages
- 13-18
- ISSN
- 1556-603X (ISSN-L)
- OpenAlex
- W1998399571
- Cited by
- 1,121
- References
- 11
- FWCI
- 16.95
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
