Xin Zhao | SigPort

Skip to main content

IEEE.org
IEEE Xplore Digital Library
IEEE Standards
IEEE Spectrum
More Sites

About SigPort
Login
Create Account

Documents
Events
Submit Your Work
Search

Xin Zhao

Primary tabs

View(active tab)
Track

Author's Documents

DEEP LEARNING VS. TRADITIONAL ALGORITHMS FOR SALIENCY PREDICTION OF DISTORTED IMAGES

2 November 2020 - 5:15pm 173 Downloads

Read More

SigPort hosts manuscripts, reports, theses, and supporting materials of interests to the broad signal processing community and provide contributors early and broad exposure.

Submit Your Work

All users may submit a standard dataset up to 2TB free of charge. Submit an Open Access dataset to allow free access to all users, or create a data competition and manage access and submissions.

Events

Find slides, presentations, posters, and other documents from Signal Processing events and conferences.

Home
About
Help
Login
Create an IEEE Account
Contact Us
Accessibility
Nondiscrimination
IEEE Ethics Reporting
Privacy Policy
Terms of Use

© Copyright 2024 IEEE – All rights reserved. Use of this website signifies your agreement to the IEEE Terms and Conditions. A public charity, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.