Improving Representation of High-frequency Components for Medical Visual Foundation Models

Improving Representation of High-frequency Components for Medical Visual Foundation Models

19 July 2024

Chao Huang

Xin Gao

Papers citing "Improving Representation of High-frequency Components for Medical Visual Foundation Models"

6 / 6 papers shown

Title
Flow Along the K-Amplitude for Generative Modeling Weitao Du Shuning Chang Jiasheng Tang Yu Rong F. Wang Shengchao Liu 46 0 0 27 Apr 2025
What Do Self-Supervised Vision Transformers Learn? Namuk Park Wonjae Kim Byeongho Heo Taekyung Kim Sangdoo Yun SSL 65 76 1 01 May 2023
Scale-MAE: A Scale-Aware Masked Autoencoder for Multiscale Geospatial Representation Learning Colorado Reed Ritwik Gupta Shufan Li S. Brockman Christopher Funk Brian Clipp Kurt Keutzer Salvatore Candido M. Uyttendaele Trevor Darrell 113 165 0 30 Dec 2022
Uniform Masking: Enabling MAE Pre-training for Pyramid-based Vision Transformers with Locality Xiang Li Wenhai Wang Lingfeng Yang Jian Yang 95 73 0 20 May 2022
Masked Autoencoders Are Scalable Vision Learners Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 258 7,337 0 11 Nov 2021
MedMNIST v2 -- A large-scale lightweight benchmark for 2D and 3D biomedical image classification Jiancheng Yang Rui Shi D. Wei Zequan Liu Lin Zhao B. Ke Hanspeter Pfister Bingbing Ni VLM 161 634 0 27 Oct 2021