Fangjun Luan1,2,3, Xuewen Mu1,2,3, Shuai Yuan1,2,3,*
CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 695-712, 2024, DOI:10.32604/cmc.2024.048502
Abstract Online Signature Verification (OSV), as a personal identification technology, is widely used in various industries. However, it faces challenges, such as incomplete feature extraction, low accuracy, and computational heaviness. To address these issues, we propose a novel approach for online signature verification, using a one-dimensional Ghost-ACmix Residual Network (1D-ACGRNet), which is a Ghost-ACmix Residual Network that combines convolution with a self-attention mechanism and performs improvement by using Ghost method. The Ghost-ACmix Residual structure is introduced to leverage both self-attention and convolution mechanisms for capturing global feature information and extracting local information, effectively complementing whole and local signature features and mitigating… More >
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