Image de couverture de livre

Test-Time Mixup Augmentation for Data and Class-Specific Uncertainty Estimation in Deep Learning Image Classification

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Lee, Hansang, Lee, Haeil, Hong, Helen, Kim, Junmo
Format:	Preprint
Publié:	2022
Sujets:	Computer Vision and Pattern Recognition Artificial Intelligence
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

The Effects of Mixed Sample Data Augmentation are Class Dependent
par: Lee, Haeil, et autres
Publié: (2023)

Noisy Label Classification using Label Noise Selection with Test-Time Augmentation Cross-Entropy and NoiseMix Learning
par: Lee, Hansang, et autres
Publié: (2022)

GenMix: Combining Generative and Mixture Data Augmentation for Medical Image Classification
par: Lee, Hansang, et autres
Publié: (2024)

Beta Sampling is All You Need: Efficient Image Generation Strategy for Diffusion Models using Stepwise Spectral Analysis
par: Lee, Haeil, et autres
Publié: (2024)

Do Vision Models Encode Object-Level Semantic Relatedness? A Cognitive Psychology-Inspired Benchmark
par: Lee, Hansang, et autres
Publié: (2017)

Inspecting Explainability of Transformer Models with Additional Statistical Information
par: Nguyen, Hoang C., et autres
Publié: (2023)

GradMix: Gradient-based Selective Mixup for Robust Data Augmentation in Class-Incremental Learning
par: Kim, Minsu, et autres
Publié: (2025)

Enhancing Generalization in Data-free Quantization via Mixup-class Prompting
par: Park, Jiwoong, et autres
Publié: (2025)

Pygmalion Effect in Vision: Image-to-Clay Translation for Reflective Geometry Reconstruction
par: Lee, Gayoung, et autres
Publié: (2025)

IWP: Token Pruning as Implicit Weight Pruning in Large Vision Language Models
par: Lee, Dong-Jae, et autres
Publié: (2026)

AH-OCDA: Amplitude-based Curriculum Learning and Hopfield Segmentation Model for Open Compound Domain Adaptation
par: Choi, Jaehyun, et autres
Publié: (2024)

IMSE: Intrinsic Mixture of Spectral Experts Fine-tuning for Test-Time Adaptation
par: Baek, Sunghyun, et autres
Publié: (2026)

Enhance Image Classification via Inter-Class Image Mixup with Diffusion Model
par: Wang, Zhicai, et autres
Publié: (2024)

Open Set Recognition for Endoscopic Image Classification: A Deep Learning Approach on the Kvasir Dataset
par: Moazzami, Kasra, et autres
Publié: (2025)

SGD-Mix: Enhancing Domain-Specific Image Classification with Label-Preserving Data Augmentation
par: Dong, Yixuan, et autres
Publié: (2025)

Intra-Cluster Mixup: An Effective Data Augmentation Technique for Complementary-Label Learning
par: Mai, Tan-Ha, et autres
Publié: (2025)

DeFloMat: Detection with Flow Matching for Stable and Efficient Generative Object Localization
par: Lee, Hansang, et autres
Publié: (2025)

SupReMix: Supervised Contrastive Learning for Medical Imaging Regression with Mixup
par: Wu, Yilei, et autres
Publié: (2023)

ContextMix: A context-aware data augmentation method for industrial visual inspection systems
par: Kim, Hyungmin, et autres
Publié: (2024)

Self-supervised Transformation Learning for Equivariant Representations
par: Yu, Jaemyung, et autres
Publié: (2025)

MATE: Meet At The Embedding -- Connecting Images with Long Texts
par: Jang, Young Kyun, et autres
Publié: (2024)

Harnessing Shared Relations via Multimodal Mixup Contrastive Learning for Multimodal Classification
par: Kumar, Raja, et autres
Publié: (2024)

A Survey on Mixup Augmentations and Beyond
par: Jin, Xin, et autres
Publié: (2024)

Pseudo-Bag Mixup Augmentation for Multiple Instance Learning-Based Whole Slide Image Classification
par: Liu, Pei, et autres
Publié: (2023)

Cross-Axis Feature Fusion with Joint-Wise Motion Difference Prediction for Text-Based 3D Human Motion Editing
par: Han, Gyojin, et autres
Publié: (2026)

Learning Question-Aware Keyframe Selection with Synthetic Supervision for Video Question Answering
par: Kwon, Minchan, et autres
Publié: (2026)

Feature Augmentation based Test-Time Adaptation
par: Cho, Younggeol, et autres
Publié: (2024)

Enhanced Multi-Class Classification of Gastrointestinal Endoscopic Images with Interpretable Deep Learning Model
par: Kamble, Astitva, et autres
Publié: (2025)

Cross-Domain Few-Shot Learning for Hyperspectral Image Classification Based on Mixup Foundation Model
par: Paeedeh, Naeem, et autres
Publié: (2026)

Physically Guided Visual Mass Estimation from a Single RGB Image
par: Lee, Sungjae, et autres
Publié: (2026)

Classification Matters: Improving Video Action Detection with Class-Specific Attention
par: Lee, Jinsung, et autres
Publié: (2024)

GeMix: Conditional GAN-Based Mixup for Improved Medical Image Augmentation
par: Carlesso, Hugo, et autres
Publié: (2025)

DCSCR: A Class-Specific Collaborative Representation based Network for Image Set Classification
par: Gao, Xizhan, et autres
Publié: (2025)

Decoupled Data Augmentation for Improving Image Classification
par: Chen, Ruoxin, et autres
Publié: (2024)

DomCLP: Domain-wise Contrastive Learning with Prototype Mixup for Unsupervised Domain Generalization
par: Lee, Jin-Seop, et autres
Publié: (2024)

ACIL: Active Class Incremental Learning for Image Classification
par: Bhattacharya, Aditya R., et autres
Publié: (2026)

Colorful Cutout: Enhancing Image Data Augmentation with Curriculum Learning
par: Choi, Juhwan, et autres
Publié: (2024)

Frequency-Aware Token Reduction for Efficient Vision Transformer
par: Lee, Dong-Jae, et autres
Publié: (2025)

AETTA: Label-Free Accuracy Estimation for Test-Time Adaptation
par: Lee, Taeckyung, et autres
Publié: (2024)

Completely Weakly Supervised Class-Incremental Learning for Semantic Segmentation
par: Kim, David Minkwan, et autres
Publié: (2025)