Random Gaussian Blur
Description
Random Gaussian Blur is an image data augmentation technique where we randomly blur the image using a Gaussian distribution.
Image Source: Wikipedia
Papers Using This Method
Probabilistic Variational Contrastive Learning2025-06-11scSSL-Bench: Benchmarking Self-Supervised Learning for Single-Cell Data2025-06-10Circumventing Backdoor Space via Weight Symmetry2025-06-09SSPS: Self-Supervised Positive Sampling for Robust Self-Supervised Speaker Verification2025-05-20Representation Learning via Non-Contrastive Mutual Information2025-04-23Impact of Language Guidance: A Reproducibility Study2025-04-10Unsupervised Detection of Fraudulent Transactions in E-commerce Using Contrastive Learning2025-03-24A Statistical Theory of Contrastive Learning via Approximate Sufficient Statistics2025-03-21SinSim: Sinkhorn-Regularized SimCLR2025-02-13Dataset Ownership Verification in Contrastive Pre-trained Models2025-02-11Self-Supervised Frameworks for Speaker Verification via Bootstrapped Positive Sampling2025-01-29Enhancing Contrastive Learning Inspired by the Philosophy of "The Blind Men and the Elephant"2024-12-21Self-Supervised Radiograph Anatomical Region Classification -- How Clean Is Your Real-World Data?2024-12-20Maximising Histopathology Segmentation using Minimal Labels via Self-Supervision2024-12-19AmCLR: Unified Augmented Learning for Cross-Modal Representations2024-12-10Mitigating Instance-Dependent Label Noise: Integrating Self-Supervised Pretraining with Pseudo-Label Refinement2024-12-06Tight PAC-Bayesian Risk Certificates for Contrastive Learning2024-12-04Explorations in Self-Supervised Learning: Dataset Composition Testing for Object Classification2024-12-01Breccia and basalt classification of thin sections of Apollo rocks with deep learning2024-10-28Accelerating Augmentation Invariance Pretraining2024-10-27