Improving Deep Learning for Maritime Remote Sensing through Data Augmentation and Latent Space

Improving Deep Learning for Maritime Remote Sensing through Data Augmentation and Latent Space

Training deep learning models requires having the right data for the problem and understanding both your data and the models’ performance on that data. Training deep learning models is difficult when data are limited, so in this paper, we seek to answer the following question: how can we train a dee...

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Bibliographic Details
Main Authors: Daniel Sobien, Erik Higgins, Justin Krometis, Justin Kauffman, Laura Freeman
Format: Article
Language:English
Published: MDPI AG 2022-07-01
Series:Machine Learning and Knowledge Extraction
Subjects:
data augmentation
dimensionality reduction
latent space
UMAP
simulated data
deep neural network
Online Access:https://www.mdpi.com/2504-4990/4/3/31

Internet

https://www.mdpi.com/2504-4990/4/3/31

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