ManuScript Details
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Paper Id:
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IJARW2190
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Title:
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OVERVIEW ON STATE-OF-THE-ART DEEP LEARNING-BASED MODELS FOR IMBALANCE CLASSIFICATION
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| Published in: |
International Journal Of All Research Writings |
| Publisher: |
IJARW |
| ISSN: |
2582-1008 |
| Volume / Issue: |
Volume 6 Issue 1 |
| Pages: |
7
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| Published On: |
7/10/2024 1:37:52 AM (MM/dd/yyyy) |
Main Author Details
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Name:
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Trang Phung T. Thu |
| Institute: |
School of Foreign Languages |
Co - Author Details
| Author Name |
Author Institute |
| Duong Ngoc Khang |
School of Foreign Languages |
Abstract
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Research Area:
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Artificial Intelligence |
| KeyWord: |
Deep learning, Imbalance classification, Long-tailed classification |
| Abstract: |
In recent years, the problem of data imbalance has become a major challenge, significantly impacting the process of mining information from data. This often happens when some classes have significantly larger samples than other classes. With the development of deep learning, there have been significant advances in representing and understanding information from images. However, when applying deep learning to practical image recognition tasks, the problem of "deep long-tail" becomes apparent. Training models to face even rare cases helps create robust and flexible models that are able to adapt well to real-world data fluctuations. This paper aims to comprehensively analyze the long-tail problem in image recognition, summarize the highlights and limitations of previous methods, and provide a view on future research directions. |
Citations
Copy and paste a formatted citation or use one of the links to import into a bibliography manager and reference.
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IEEE
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Trang Phung T. Thu, Duong Ngoc Khang, "OVERVIEW ON STATE-OF-THE-ART DEEP LEARNING-BASED MODELS FOR IMBALANCE CLASSIFICATION", International Journal Of All Research Writings,
vol. 6, no. 1, pp. 14-20, 2024.
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MLA
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Trang Phung T. Thu, Duong Ngoc Khang "OVERVIEW ON STATE-OF-THE-ART DEEP LEARNING-BASED MODELS FOR IMBALANCE CLASSIFICATION." International Journal Of All Research Writings,
vol 6, no. 1, 2024, pp. 14-20.
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APA
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Trang Phung T. Thu, Duong Ngoc Khang (2024). OVERVIEW ON STATE-OF-THE-ART DEEP LEARNING-BASED MODELS FOR IMBALANCE CLASSIFICATION. International Journal Of All Research Writings,
6(1), 14-20.
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OVERVIEW ON STATE-OF-THE-ART DEEP LEARNING-BASED MODELS FOR IMBALANCE CLASSIFICATION
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OVERVIEW ON STATE-OF-THE-ART DEEP LEARNING-BASED MODELS FOR IMBALANCE CLASSIFICATION
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