目前,无监督单模态行人重识别研究主要集中于可见光图像。随着新型红外摄像头的普及,无监督红外行人重识别也展现出其研究价值。由于红外图像对比度低、缺乏颜色纹理细节信息,因此全局信息对于红外行人重识别至关重要。本文设计了基于F-...目前,无监督单模态行人重识别研究主要集中于可见光图像。随着新型红外摄像头的普及,无监督红外行人重识别也展现出其研究价值。由于红外图像对比度低、缺乏颜色纹理细节信息,因此全局信息对于红外行人重识别至关重要。本文设计了基于F-ResGAM的无监督红外行人重识别网络。该网络首先利用小波变换对图像进行预处理以增强特征提取能力,接着在resnet50网络结构中引入全局注意力机制(Global Attention Mechanism,GAM)关注更多的全局信息。此外,由于红外伪标签噪声较大,本文提出采用基于样本扩展的分组采样(Group Sampling based on Sample Expansion,GSSE)策略进一步优化伪标签生成,从而提升了模型的识别精度。实验结果表明,本文提出的优化方法有效提升了无监督红外行人重识别的精度,尤其是rank指标显著提升。展开更多
For any fixed ε > 0, an explicit construction of anorthonormal trigonometric polynomial basis {Tk}∞k=1 inL2 [0,1) with degTk≤ 0.5(1 +ε)k is presented. Thus weimprove the results obtained by D. Offin and K. Osko...For any fixed ε > 0, an explicit construction of anorthonormal trigonometric polynomial basis {Tk}∞k=1 inL2 [0,1) with degTk≤ 0.5(1 +ε)k is presented. Thus weimprove the results obtained by D. Offin and K. Oskolkov in [4] and by Al. A. Privalov in [6]. and practically solve the open problemasked in [4], [8] and [9]. Moreover, as in [4], Fourier sums with respectto this polynomial basis are projectors onto subspaces of trigonometricpolynomials of high degree, which implies almost best approximation- properties.展开更多
文摘目前,无监督单模态行人重识别研究主要集中于可见光图像。随着新型红外摄像头的普及,无监督红外行人重识别也展现出其研究价值。由于红外图像对比度低、缺乏颜色纹理细节信息,因此全局信息对于红外行人重识别至关重要。本文设计了基于F-ResGAM的无监督红外行人重识别网络。该网络首先利用小波变换对图像进行预处理以增强特征提取能力,接着在resnet50网络结构中引入全局注意力机制(Global Attention Mechanism,GAM)关注更多的全局信息。此外,由于红外伪标签噪声较大,本文提出采用基于样本扩展的分组采样(Group Sampling based on Sample Expansion,GSSE)策略进一步优化伪标签生成,从而提升了模型的识别精度。实验结果表明,本文提出的优化方法有效提升了无监督红外行人重识别的精度,尤其是rank指标显著提升。
文摘For any fixed ε > 0, an explicit construction of anorthonormal trigonometric polynomial basis {Tk}∞k=1 inL2 [0,1) with degTk≤ 0.5(1 +ε)k is presented. Thus weimprove the results obtained by D. Offin and K. Oskolkov in [4] and by Al. A. Privalov in [6]. and practically solve the open problemasked in [4], [8] and [9]. Moreover, as in [4], Fourier sums with respectto this polynomial basis are projectors onto subspaces of trigonometricpolynomials of high degree, which implies almost best approximation- properties.
