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首页> 外文会议>2016 International Conference on Biometrics >User individuality based cost-sensitive learning: A case study in finger vein recognition
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User individuality based cost-sensitive learning: A case study in finger vein recognition

机译：基于用户个性的成本敏感型学习：手指静脉识别的案例研究

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摘要

State-of-the-art cost-sensitive learning based techniques in biometrics ignore cost difference between users and determine the loss only based on the misrecognition category. In practice, this may not always hold and the user individuality may also affect the loss of misrecognition. For example, misrecognizing an imposter as an administrator can cause a much more serious loss than misrecognizing it as a normal user. At the same time, two administratorsormal users may have different probability to accept imposter. To confidently prevent the high-probability error, the cost of false acceptance for one user with a high probability should be larger than it for the other users. To make cost definition more reasonable and further lower misrecognition cost of a recognition system, we propose to incorporate the user individuality, i.e., user role and user gullibility, into the traditional cost-sensitive learning model through defining an improved object function. By employing the new model, we further develop a user role and gullibility based mckNN (rg-mckNN). Experimental results on finger vein databases demonstrate the effectiveness of the proposed method.
机译：生物识别技术中基于成本敏感的最新学习技术忽略了用户之间的成本差异，仅根据误识别类别确定损失。实际上，这可能并不总是成立，并且用户个性也可能影响误识别的损失。例如，将冒名顶替者错误地识别为管理员，比将其错误识别为普通用户会导致更严重的损失。同时，两个管理员/普通用户接受冒名顶替者的可能性可能不同。为了可靠地防止高概率错误，对于一个具有高概率的用户，错误接受的代价应大于对其他用户的错误接受。为了使成本定义更加合理并进一步降低识别系统的误识别成本，我们建议通过定义改进的对象功能，将用户个性即用户角色和用户可混性纳入传统的成本敏感型学习模型中。通过使用新模型，我们进一步开发了基于用户角色和可信任性的mckNN（rg-mckNN）。在手指静脉数据库上的实验结果证明了该方法的有效性。

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