Global Contrast Masked Autoencoders Are Powerful Pathological Representation Learners

18 May 2022

Papers citing "Global Contrast Masked Autoencoders Are Powerful Pathological Representation Learners"

8 / 8 papers shown

Title
A Survey of the Self Supervised Learning Mechanisms for Vision Transformers Asifullah Khan A. Sohail M. Fiaz Mehdi Hassan Tariq Habib Afridi ... Muhammad Zaigham Zaheer Kamran Ali Tangina Sultana Ziaurrehman Tanoli Naeem Akhter 41 3 0 30 Aug 2024
Self Pre-training with Topology- and Spatiality-aware Masked Autoencoders for 3D Medical Image Segmentation Pengfei Gu Yejia Zhang Huimin Li Chaoli Wang D. Z. Chen MedIm 42 1 0 15 Jun 2024
Aerial Image Object Detection With Vision Transformer Detector (ViTDet) Liya Wang A. Tien 30 7 0 28 Jan 2023
A Survey on Masked Autoencoder for Self-supervised Learning in Vision and Beyond Chaoning Zhang Chenshuang Zhang Junha Song John Seon Keun Yi Kang Zhang In So Kweon SSL 42 70 0 30 Jul 2022
Masked Autoencoders Are Scalable Vision Learners Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 258 7,412 0 11 Nov 2021
Self-supervised learning methods and applications in medical imaging analysis: A survey Saeed Shurrab R. Duwairi OOD 32 173 0 17 Sep 2021
Improved Baselines with Momentum Contrastive Learning Xinlei Chen Haoqi Fan Ross B. Girshick Kaiming He SSL 238 3,359 0 09 Mar 2020
A Survey on Deep Learning in Medical Image Analysis G. Litjens Thijs Kooi B. Bejnordi A. Setio F. Ciompi Mohsen Ghafoorian Jeroen van der Laak Bram van Ginneken C. I. Sánchez OOD 278 10,599 0 19 Feb 2017