首页|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)
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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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.”
ChongqingPeople’s Republic of ChinaA siaCyborgsEmerging TechnologiesMachine LearningChongqing University of Posts and Telecommunications
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