基于少量镜头识别技术的实时人脸识别研究

2018 3rd International Conference on Contemporary Computing and Informatics (IC3I) Pub Date : 2018-10-01 DOI:10.1109/IC3I44769.2018.9007247

Paramveer Singh, S. Srivastava, A. Rai, A. Cheema

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引用次数: 0

摘要

本文旨在用很少的例子来研究人脸识别问题。人脸识别是一个棘手的问题，但在许多实际应用中都很重要。现代技术需要成千上万的样本才能有效地识别它们。然而，构建这样的数据集在实际应用中并不总是可行的。因此，我们在具有标准评估指标的基准数据集上分析了这些技术在较少的镜头学习范式下的有效性。

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Study of real time face recognition using few shot recognition techniques

This paper aims at studying the problem of face recognition using very few examples. Face recognition is a tough problem yet is important for several practical applications. Contemporary techniques require thousands of samples to recognize them effectively. However, constructing such a dataset is not always feasible for practical applications. Therefore, we analyze the effectiveness of such techniques with few shot learning paradigms on benchmark datasets with standard evaluation metrics.

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2018 3rd International Conference on Contemporary Computing and Informatics (IC3I)

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