SaliencyMix+: Noise-Minimized Image Mixing Method With Saliency Map in Data Augmentation
Data augmentation is vital in deep learning for enhancing model robustness by artificially expanding training datasets. However, advanced methods like CutMix blend images and assign labels based on pixel ratios, often introducing label noise by neglecting the significance of blended regions, and Sal...
Saved in:
Main Authors: | Hajeong Lee, Zhixiong Jin, Jiyoung Woo, Byeongjoon Noh |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10858701/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Question Sequences and Salience in TED Talks
by: Michele Cardo, et al.
Published: (2024-08-01) -
Improvement of CRF-Based Saliency Detection Algorithm Using Matrix Decomposition Based Features
by: Mohammad Shouryabi, et al.
Published: (2020-09-01) -
The Effects of Type of Instruction of English Prepositions with Varying Degrees of Salience
by: Ana Mónica Preciado-Sánchez, et al.
Published: (2024-11-01) -
Harmony versus Voicing. Modeling Local-Level Salience and Stability in Jazz after 1960
by: Rich Pellegrin
Published: (2022-07-01) -
L’emploi d’expressions métalangagières : phénomènes de saillance et travail interprétatif
by: Blandine Pennec
Published: (2014-10-01)