This paper aims to determine the optimal fines content of coarse-grained soil required to simultaneously achieve weaker frost susceptibility and better bearing capacity. We studied the frost susceptibility and strengt...This paper aims to determine the optimal fines content of coarse-grained soil required to simultaneously achieve weaker frost susceptibility and better bearing capacity. We studied the frost susceptibility and strength properties of coarse-grained soil by means of frost heaving tests and static triaxial tests, and the results are as follows: (1) the freezing temperature of coarse-grained soil decreased gradually and then leveled off with incremental increases in the percent content of fines; (2) the fines content proved to be an important factor influencing the frost heave susceptibility and strength properties of coarse-grained soil. With incremental increases in the percent content of fines, the frost heave ratio increased gradually and the cohesion function of fines effectively enhanced the shear strength of coarse-grained soil before freeze-thaw, but the frost susceptibility of fines weakened the shear strength of coarse-grained soil after freeze-thaw; (3) with increasing numbers of freeze-thaw cycles, the shear strength of coarse-grained soil decreased and then stabilized after the ninth freeze-thaw cycle, and therefore the mechanical indexes of the ninth freeze-thaw cycle are recommended for the engi- neering design values; and (4) considering frost susceptibility and strength properties as a whole, the optimal fines content of 5% is recommended for railway sub,fade coarse-~rained soil fillings in frozen re^ions.展开更多
针对行人检测系统中存在的难以同时具有较高的检测率和较快的检测速度这一问题,本文提出了一种自适应Coarse-to-Fine Deformable Part Model(CtF DPM)的行人检测模型.首先,将低分辨率根滤波器特征提取得分与阈值进行比较,以确定高分辨...针对行人检测系统中存在的难以同时具有较高的检测率和较快的检测速度这一问题,本文提出了一种自适应Coarse-to-Fine Deformable Part Model(CtF DPM)的行人检测模型.首先,将低分辨率根滤波器特征提取得分与阈值进行比较,以确定高分辨率部件滤波器的特征提取区域;随后,在同分辨率层中引入同级约束关系,增强同层的特征相关性;最后,将该特征提取与其他多种算法在INRIA数据库中进行检测准确性测试,并与隐式支持向量机(LSVM)结合进行实际道路环境测试.理论性能和实际测试结果表明:基于自适应CtF DPM的行人检测模型在保证检测性能的同时,特征提取时间可降至十几毫秒,显著提高了检测速度.展开更多
跨模态行人重识别研究的重难点主要来自于行人图像之间巨大的模态差异和模态内差异。针对这些问题,提出一种结合多尺度特征与混淆学习的网络结构。为实现高效的特征提取、缩小模态内差异,将网络设计为多尺度特征互补的形式,分别学习行...跨模态行人重识别研究的重难点主要来自于行人图像之间巨大的模态差异和模态内差异。针对这些问题,提出一种结合多尺度特征与混淆学习的网络结构。为实现高效的特征提取、缩小模态内差异,将网络设计为多尺度特征互补的形式,分别学习行人的局部细化特征与全局粗糙特征,从细粒度和粗粒度两方面来增强网络的特征表达能力。利用混淆学习策略,模糊网络的模态识别反馈,挖掘稳定且有效的模态无关属性应对模态差异,来提高特征对模态变化的鲁棒性。在大规模数据集SYSU-MM01的全搜索模式下该算法首位击中率和平均精度(mean average precision,mAP)的结果分别为76.69%和72.45%,在RegDB数据集的可见光到红外模式下该算法首位击中率和mAP的结果分别为94.62%和94.60%,优于现有的主要方法,验证了所提方法的有效性。展开更多
基金supported by the National Key Technology Support Program of China (No.2012BAG05B00)the National Natural Science Foundation of China (Nos. 51208320 and 51178281)the Key Subject of China Railway Corporation (Nos. 2014G003-F and 2014G003-A)
文摘This paper aims to determine the optimal fines content of coarse-grained soil required to simultaneously achieve weaker frost susceptibility and better bearing capacity. We studied the frost susceptibility and strength properties of coarse-grained soil by means of frost heaving tests and static triaxial tests, and the results are as follows: (1) the freezing temperature of coarse-grained soil decreased gradually and then leveled off with incremental increases in the percent content of fines; (2) the fines content proved to be an important factor influencing the frost heave susceptibility and strength properties of coarse-grained soil. With incremental increases in the percent content of fines, the frost heave ratio increased gradually and the cohesion function of fines effectively enhanced the shear strength of coarse-grained soil before freeze-thaw, but the frost susceptibility of fines weakened the shear strength of coarse-grained soil after freeze-thaw; (3) with increasing numbers of freeze-thaw cycles, the shear strength of coarse-grained soil decreased and then stabilized after the ninth freeze-thaw cycle, and therefore the mechanical indexes of the ninth freeze-thaw cycle are recommended for the engi- neering design values; and (4) considering frost susceptibility and strength properties as a whole, the optimal fines content of 5% is recommended for railway sub,fade coarse-~rained soil fillings in frozen re^ions.
文摘跨模态行人重识别研究的重难点主要来自于行人图像之间巨大的模态差异和模态内差异。针对这些问题,提出一种结合多尺度特征与混淆学习的网络结构。为实现高效的特征提取、缩小模态内差异,将网络设计为多尺度特征互补的形式,分别学习行人的局部细化特征与全局粗糙特征,从细粒度和粗粒度两方面来增强网络的特征表达能力。利用混淆学习策略,模糊网络的模态识别反馈,挖掘稳定且有效的模态无关属性应对模态差异,来提高特征对模态变化的鲁棒性。在大规模数据集SYSU-MM01的全搜索模式下该算法首位击中率和平均精度(mean average precision,mAP)的结果分别为76.69%和72.45%,在RegDB数据集的可见光到红外模式下该算法首位击中率和mAP的结果分别为94.62%和94.60%,优于现有的主要方法,验证了所提方法的有效性。