Mr. Jin Liu Profile

Jin Liu

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 | 27 September 2022 Paper

Facial expression recognition based on improved residual network

Jin Liu, Xiaoshu Luo, Yuanqin Huang

Proceedings Volume 12346, 123461H (2022) https://doi.org/10.1117/12.2653443

KEYWORDS: Convolution, Facial recognition systems, Feature extraction

Read Abstract +

A facial expression recognition method with improved residual network is proposed to address the problems of low recognition accuracy and loss of detailed features in the discriminative task due to inappropriate pooling in current facial expression recognition models. First, multi-scale importance pooling with adaptively learned input feature weights is proposed to improve the model's ability to retain and recognize global features. Second, asymmetric convolution is used to augment the convolution kernels to improve the characterization of local features, and the set of asymmetric convolution kernels trained to convergence is fused and equivalently converted to the original network structure to avoid introducing additional parameter optimization in the inference stage. Finally, the expression recognition accuracies of 85.53% and 72.72% were achieved in two publicly available datasets, RAF-DB and FER2013, respectively, and the experimental results demonstrate the effectiveness of the proposed method with certain application prospects.

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