首页近三年深度学习掌纹分类方法有什么，至少10个

近三年深度学习掌纹分类方法有什么，至少10个

时间: 2024-02-26 09:54:19 浏览: 133

Deep Learning in Biometrics

Deep Learning is now synonymous with applied machine learning. Many technology giants (e.g. Google, Microsoft, Apple, IBM) as well as start-ups are focusing on deep learning-based techniques for data analytics and artificial intelligence. This technology applies quite strongly to biometrics. This book covers topics in deep learning, namely convolutional neural networks, deep belief network and stacked autoencoders. The focus is also on the application of these techniques to various biometric modalities: face, iris, palmprint, and fingerprints, while examining the future trends in deep learning and biometric research.

以下是近三年深度学习掌纹分类方法的一些例子： 1. "Palmprint recognition using deep learning with spatial pyramid pooling" - 2019年 2. "Palmprint recognition using deep learning with multi-scale convolutional neural networks" - 2018年 3. "Palmprint recognition with convolutional neural networks and a Siamese architecture" - 2018年 4. "Palmprint recognition using convolutional neural networks with transfer learning" - 2018年 5. "Palmprint recognition using deep learning with graph embedding" - 2018年 6. "Palmprint recognition using deep learning with adaptive feature pooling" - 2017年 7. "Palmprint recognition using deep learning with convolutional neural networks and a fusion strategy" - 2017年 8. "Palmprint recognition using deep learning with local binary pattern features" - 2017年 9. "Palmprint recognition using deep learning with feature fusion" - 2017年 10. "Palmprint recognition using deep learning with sparse representation" - 2017年这些方法主要利用了卷积神经网络、深度学习和特征融合等技术，提高了掌纹识别的准确性和鲁棒性。

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