Prof. Tao Gong Profile

Prof. Tao Gong

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 13 September 2024 Paper

Enhanced hard negative synthesis for contrastive learning in skin lesion classification

Xue Zhang, Kaida Jiang, Li Quan, Tao Gong

Proceedings Volume 13254, 132541V (2024) https://doi.org/10.1117/12.3039105

KEYWORDS: Skin, Machine learning, Image classification, Data modeling, Projection systems, Statistical modeling

Read Abstract +

The analysis of skin lesion dermoscopic images has traditionally relied on supervised learning paradigms, necessitating extensive labeled datasets which can be costly and time-consuming for dermatologists. Conversely, the abundance of unlabeled data offers a promising avenue for self-supervised learning methods in this field. In this work, we introduce a novel strategy for hard negative synthesis that bolsters the efficacy of contrastive learning in skin lesion classification. By strategically down-weighting the contribution of the hardest negative samples during feature-level mixing, our method ensures the neural network prioritizes learning from the most informative and reliable negatives, thereby enhancing the model's feature learning ability. After fine-tuning with a limited set of labeled data, our method demonstrates notable superiority on the ISIC-2016 classification dataset, achieving a 4.29% increase in ROC AUC and a 5.39% increase in F1 score over the standard MoCo-v2 framework.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years