Robotics & Machine Learning Daily News2024,Issue(Sep.3) :27-28.

Studies from Chongqing University of Posts and Telecommunications Describe New F indings in Machine Learning (A Method for Recovering Adversarial Samples With Bo th Adversarial Attack Forensics and Recognition Accuracy)

Robotics & Machine Learning Daily News2024,Issue(Sep.3) :27-28.

Studies from Chongqing University of Posts and Telecommunications Describe New F indings in Machine Learning (A Method for Recovering Adversarial Samples With Bo th Adversarial Attack Forensics and Recognition Accuracy)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – A new study on Machine Learning is now available. According to news reportingoriginating from Chongqing, People’s Rep ublic of China, by NewsRx correspondents, research stated,“Adversarial samples deceive machine learning models through small but elaborate modifications that lead to erroneous outputs. The severity of the adversarial sample problem has com e to the forefront withthe widespread use of machine learning in areas such as security systems, autonomous driving, speechrecognition, finance, and medical d iagnostics.”

Key words

Chongqing/People’s Republic of China/A sia/Cyborgs/Emerging Technologies/Machine Learning/Chongqing University of Posts and Telecommunications

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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