Work

F2PQNN: a fast and secure two-party inference on quantized convolutional neural networks

Year: 2025

Type: article

Source: The Computer Journal

DOI: 10.1093/comjnl/bxaf019

Authors: Jinguo Li, Peichun Yuan, Jin Zhang, Sheng Shen, Yin He, Ruyang Xiao

Institutions: Shanghai University of Electric Power, Changsha University of Science and Technology, University of California, Santa Barbara

Language: English

Topic: Cryptography and Data Security

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: closed

Funder: National Natural Science Foundation of China

Award: G1611947856

OpenAlex ID: W4409111838

FWCI: 0.408

Cites: 51

Cited by: 1

Related to: 10