Large Tensor Analysis and Applications

Tensor analysis is a fundamental task for processing multi-dimensional data. This approach not only has ubiquitous applications in a range of different fields – including image processing, computer vision, and machine/deep learning – but also has its own theoretical foundations with the potential to nurture new methods with more advanced performance. However, the barriers between subject disciplines hinder communication between researchers with different research backgrounds. This lack of communication, to some extent, limits the power of state-of-the-art tensor analysis techniques in different fields, and restricts the development and applications of new and more powerful methods. Recent studies have shown promising advancements in tensor decomposition, approximation, and regression, yet the integration of these techniques across various domains remains underexplored. Addressing these interdisciplinary gaps is crucial for leveraging the full potential of tensor analysis.

This Research Topic aims to bring together the research challenges related to tensor analysis in different fields to break down the subject barriers and deliver interdisciplinary solutions and applications. Therefore, all contributions related to tensor analysis are welcome, including theoretical analyses, methodologies, algorithms, and applications in different fields. Specific questions to be addressed include: How can tensor analysis techniques be adapted for diverse applications? What are the most effective methods for tensor decomposition and factorization? How can tensor analysis be integrated with deep learning frameworks to enhance performance?

To gather further insights in the interdisciplinary applications of tensor analysis, we welcome articles addressing, but not limited to, the following themes:

- Tensor decomposition/factorization
- Tensor approximation
- Tensor regression
- Tensor analysis with statistical techniques
- Tensor analysis with deep neural networks
- Applications of tensor analysis in signal processing, image processing, and computer vision
- Applications of tensor analysis in artificial intelligence
- Other applications of tensor analysis

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Clinical Trial
• Community Case Study
• Conceptual Analysis
• Curriculum, Instruction, and Pedagogy
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Clinical Trial
• Community Case Study
• Conceptual Analysis
• Curriculum, Instruction, and Pedagogy
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy and Practice Reviews
• Review
• Study Protocol
• Systematic Review
• Technology and Code

Keywords: tensor analysis, tensor application, signal processing, image processing, computer vision, machine learning, deep learning, artificial intelligence

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.