Contrastive learning improves representation and transferability of diabetic retinopathy classification models

被引：0
|
作者：
Alam, Minhaj Nur [1 ,2 ]
Leng, Theodore [3 ]
Hallak, Joelle [2 ,4 ]
Rubin, Daniel [1 ]
机构：
[1] Stanford Univ, Sch Med, Biomed Data Sci, Stanford, CA 94305 USA
[2] Univ Illinois, Illinois Eye & Ear Infirm, Dept Ophthalmol & Visual Sci, Chicago, IL USA
[3] Stanford Univ, Sch Med, Stanford, CA 94305 USA
[4] AbbVie Inc, N Chicago, IL USA
来源：
INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE | 2022年 / 63卷 / 07期
关键词：
D O I：
暂无
中图分类号：
R77 [眼科学];
学科分类号：
100212 ;
摘要：
1156
引用
收藏
页数：3
相关论文
共 50 条
  • [41] Diabetic Retinopathy Detection Using Deep Learning Models
    Kanakaprabha, S.
    Radha, D.
    Santhanalakshmi, S.
    UBIQUITOUS INTELLIGENT SYSTEMS, 2022, 302 : 75 - 90
  • [42] A Benchmark for Studying Diabetic Retinopathy: Segmentation, Grading, and Transferability
    Zhou, Yi
    Wang, Boyang
    Huang, Lei
    Cui, Shanshan
    Shao, Ling
    IEEE TRANSACTIONS ON MEDICAL IMAGING, 2021, 40 (03) : 818 - 828
  • [43] Ensemble Models for Multi-class Classification of Diabetic Retinopathy
    Sahayam, Subin
    Manasa, Tutturu Lakshmi
    Jayaraman, Umarani
    PATTERN RECOGNITION AND MACHINE INTELLIGENCE, PREMI 2021, 2024, 13102 : 110 - 117
  • [44] Unsupervised SAR Representation Learning Improves Classification Performance
    Vaughn, Nolan
    Sullivan, Bo
    Jaskie, Kristen
    AUTOMATIC TARGET RECOGNITION XXXIV, 2024, 13039
  • [45] Detection and Classification of Diabetic Retinopathy Using DCNN and BSN Models
    Sudha, S.
    Srinivasan, A.
    Devi, T. Gayathri
    CMC-COMPUTERS MATERIALS & CONTINUA, 2022, 72 (01): : 597 - 609
  • [46] A Broad Study on the Transferability of Visual Representations with Contrastive Learning
    Islam, Ashraful
    Chen, Chun-Fu
    Panda, Rameswar
    Karlinsky, Leonid
    Radke, Richard
    Feris, Rogerio
    2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2021), 2021, : 8825 - 8835
  • [47] KMoCoL: k-Positive Momentum Contrastive Learning for Imbalanced Diabetic Retinopathy Grading
    Li, Luhu
    Liu, Xuya
    Hou, Xinguo
    Chen, Li
    Zhou, Yuanfeng
    Fu, Shujun
    IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2025, 74
  • [48] Using Deep Learning Architectures for Detection and Classification of Diabetic Retinopathy
    Mohanty, Cheena
    Mahapatra, Sakuntala
    Acharya, Biswaranjan
    Kokkoras, Fotis
    Gerogiannis, Vassilis C.
    Karamitsos, Ioannis
    Kanavos, Andreas
    SENSORS, 2023, 23 (12)
  • [49] An Ensembled Method For Diabetic Retinopathy Classification using Transfer Learning
    Attota, Dinesh
    Tadikonda, Durga Nagarjuna
    Pethe, Shruthi
    Khan, Md Abdullah Al Hafiz
    2022 IEEE 46TH ANNUAL COMPUTERS, SOFTWARE, AND APPLICATIONS CONFERENCE (COMPSAC 2022), 2022, : 1444 - 1449
  • [50] Learning protein language contrastive models with multi-knowledge representation
    Xu, Wenjun
    Xia, Yingchun
    Sun, Bifan
    Zhao, Zihao
    Tang, Lianggui
    Zhou, Obo
    Wang, Qingyong
    Gu, Lichuan
    FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2025, 164
12345