Pedestrian attribute classification from a pedestrian image captured in surveillance scenarios is challenging due to diverse clothing appearances,varied poses and different camera views. A multiscale and multi-label c...Pedestrian attribute classification from a pedestrian image captured in surveillance scenarios is challenging due to diverse clothing appearances,varied poses and different camera views. A multiscale and multi-label convolutional neural network( MSMLCNN) is proposed to predict multiple pedestrian attributes simultaneously. The pedestrian attribute classification problem is firstly transformed into a multi-label problem including multiple binary attributes needed to be classified. Then,the multi-label problem is solved by fully connecting all binary attributes to multi-scale features with logistic regression functions. Moreover,the multi-scale features are obtained by concatenating those featured maps produced from multiple pooling layers of the MSMLCNN at different scales. Extensive experiment results show that the proposed MSMLCNN outperforms state-of-the-art pedestrian attribute classification methods with a large margin.展开更多
目的:探索声音刺激试验用于胎儿听力筛查可行性。方法:对前来笔者所在医院就诊的2 231例孕妇进行声音刺激试验及其出生后的新生儿听力检测。按不同声音是否诱发出反应进行分组,其中A组为105 d B引出反应,411例;B组为110 d B引出反应,452...目的:探索声音刺激试验用于胎儿听力筛查可行性。方法:对前来笔者所在医院就诊的2 231例孕妇进行声音刺激试验及其出生后的新生儿听力检测。按不同声音是否诱发出反应进行分组,其中A组为105 d B引出反应,411例;B组为110 d B引出反应,452例;C组为115 d B引出反应,563例;D为120 d B引出反应,504例;E组为120 d B仍无法引出反应,301例。结果:A组至D组耳聋检出率上升,至E组时最高,A～D各组之间两两比较,差异均无统计学意义(P>0.05)。E组(13.29‰)显著高于A组(0)、B组(0)、C组(1.78‰)及D组(3.97‰),差异均有统计学意义(x^2=50.18、57.83、53.12、36.17,P<0.05)。结论:声音刺激试验在胎儿听力筛查可行,可供临床选择使用。展开更多
文摘本文提出一种采用尺度不变特征变换(Scale-Invariant Feature Transform,SIFT)和局部聚合向量(Vector of Locally Aggregated Descriptors,VLAD)特征编码的布匹检索算法。首先,提取图像的SIFT特征,以对图像进行特征表达。但是,每张图像SIFT特征点数量可能不同,导致不同图像的特征向量维度不一致,无法直接进行图像之间的相似度计算。为此,本文进一步对图像的SIFT特征进行VLAD编码,在保证不同图像的特征维度一致的同时,改进SIFT特征对图像的表达能力。在VLAD编码方面,先用K-means聚类算法生成视觉词典;再进行特征向量局部聚合。局部聚合过程包括:首先,计算图像中SIFT特征向量与对应视觉词之间的残差;然后,将每个视觉词相应的残差求和;最后,把各个视觉词上的残差求和值进行串联得到图像的VLAD编码。本文实验采用十次平均的累计匹配特性(Cumulative Match Characteristic,CMC)曲线作为性能指标。结果表明,本文所提出的方法能提高检索速度,且具有较高的识别率,其平均Rank 1识别率达到95.03%。
基金Supported by the National Natural Science Foundation of China(No.61602191,61672521,61375037,61473291,61572501,61572536,61502491,61372107,61401167)the Natural Science Foundation of Fujian Province(No.2016J01308)+3 种基金the Scientific and Technology Funds of Quanzhou(No.2015Z114)the Scientific and Technology Funds of Xiamen(No.3502Z20173045)the Promotion Program for Young and Middle aged Teacher in Science and Technology Research of Huaqiao University(No.ZQN-PY418,ZQN-YX403)the Scientific Research Funds of Huaqiao University(No.16BS108)
文摘Pedestrian attribute classification from a pedestrian image captured in surveillance scenarios is challenging due to diverse clothing appearances,varied poses and different camera views. A multiscale and multi-label convolutional neural network( MSMLCNN) is proposed to predict multiple pedestrian attributes simultaneously. The pedestrian attribute classification problem is firstly transformed into a multi-label problem including multiple binary attributes needed to be classified. Then,the multi-label problem is solved by fully connecting all binary attributes to multi-scale features with logistic regression functions. Moreover,the multi-scale features are obtained by concatenating those featured maps produced from multiple pooling layers of the MSMLCNN at different scales. Extensive experiment results show that the proposed MSMLCNN outperforms state-of-the-art pedestrian attribute classification methods with a large margin.
文摘目的:探索声音刺激试验用于胎儿听力筛查可行性。方法:对前来笔者所在医院就诊的2 231例孕妇进行声音刺激试验及其出生后的新生儿听力检测。按不同声音是否诱发出反应进行分组,其中A组为105 d B引出反应,411例;B组为110 d B引出反应,452例;C组为115 d B引出反应,563例;D为120 d B引出反应,504例;E组为120 d B仍无法引出反应,301例。结果:A组至D组耳聋检出率上升,至E组时最高,A～D各组之间两两比较,差异均无统计学意义(P>0.05)。E组(13.29‰)显著高于A组(0)、B组(0)、C组(1.78‰)及D组(3.97‰),差异均有统计学意义(x^2=50.18、57.83、53.12、36.17,P<0.05)。结论:声音刺激试验在胎儿听力筛查可行,可供临床选择使用。
