Learning and Adaptation From Minimum Samples With Heterogeneous Quality: An Investigation of Image Segmentation Networks on Natural Dataset

Learning and Adaptation From Minimum Samples With Heterogeneous Quality: An Investigation of Image Segmentation Networks on Natural Dataset

Training deep learning-based image segmentation networks require large number of samples of adequate quality. However, obtaining large number of samples is not possible in certain domains. Recent approaches use augmentation and transfer learning techniques to overcome small sample size. Augmentation...

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Bibliographic Details
Main Authors: V. V. Sajith Variyar, V. Sowmya, Ramesh Sivanpillai, Gregory K. Brown
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Image segmentation
less training samples
image quality
encoder-decoder networks
deep neural networks
vision transformer
Online Access:https://ieeexplore.ieee.org/document/10123932/

Internet

https://ieeexplore.ieee.org/document/10123932/

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