A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications

A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications

Abstract Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data...

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Bibliographic Details
Main Authors: Laith Alzubaidi, Jinshuai Bai, Aiman Al-Sabaawi, Jose Santamaría, A. S. Albahri, Bashar Sami Nayyef Al-dabbagh, Mohammed A. Fadhel, Mohamed Manoufali, Jinglan Zhang, Ali H. Al-Timemy, Ye Duan, Amjed Abdullah, Laith Farhan, Yi Lu, Ashish Gupta, Felix Albu, Amin Abbosh, Yuantong Gu
Format: Article
Language:English
Published: SpringerOpen 2023-04-01
Series:Journal of Big Data
Subjects:
Deep learning
Data scarcity
Machine learning
Convolutional neural network (CNN)
Deep neural network architectures
Lack of training data
Online Access:https://doi.org/10.1186/s40537-023-00727-2

Internet

https://doi.org/10.1186/s40537-023-00727-2

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