A Lightweight Face Verification Based on Adaptive Cascade Network and Triplet Loss Function

Abstract

In the past few years, with the continuous breakthrough of technology in various fields, artificial intelligence has been considered as a revolutionary technology. One of the most important and useful applications of artificial intelligence is face detection. The outbreak of COVID-19 has promoted the development of the noncontact identity authentication system. Face detection is also one of the key techniques in this kind of authentication system. However, the current real-time face detection is computationally expensive which hinders the application of face recognition. To address this issue, we propose a face verification framework based on adaptive cascade network and triplet loss. The framework is simple in network architecture and has light-weighted parameters. The training network is made of three stages with an adaptive cascade network and utilizes a novel image pyramid based on scales with different sizes. We train the face verification model and complete the verification within 0.15 second for processing one image which shows the computation efficiency of our proposed framework. In addition, the experimental results also show the competitive accuracy of our proposed framework which is around 98.6%. Using dynamic semihard triplet strategy for training, our network achieves a classification accuracy of 99.2% on the dataset of Labeled Faces in the Wild.

PPMM-DA: Privacy-Preserving Multidimensional and Multisubset Data Aggregation With Differential Privacy for Fog-Based Smart Grids

“…The experiment results show that our proposed scheme is more efficient at computational overhead and communication overhead. In future, we will study tariff problem [60], general transactive energy (TE) retailing problem [61], user access control using lightweight face verification [62], trusted entities problem by leveraging the Trusted Execution Environment (TEE) [63] to meet the requirements of fair pricing, intelligent electronic devices and user trust.…”

Retracted: A Lightweight Face Verification Based on Adaptive Cascade Network and Triplet Loss Function

“…This article has been retracted by Hindawi following an investigation undertaken by the publisher [1]. This investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process:…”