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您的检索式：作者名="CHI Hongxin"
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| 1 | The role of Chinese medicine in the treatment of chronic diseases in China显示文摘 | JIANG Miao ZHANG Chi CAO Hongxin | 2011 | Planta Medica2011，77，9： | 1 |
| 2 | Diagenesis tectonic setting and U-Pb dating for zircon from Tanjianshan Group in northern margin of Qaidam Basin显示文摘The shape,texture,content and REE characteristics of zircons from the O2tnd-1,O3tnd-2,O3tnd-3pyroclastic rock of Tanjianshan Group on the north margin of Qaidam Basin indicate that the O2-3tndis the product of volcanism during the transitional period from ocean-land interim crust to oceanic crust.The U-Pb surface ages obtained from O3tnd-2and O3tnd-3can be divided into 9 groups,every age group coincides with the period when significant tectonic-heat event took place at Oulongbuluke micro-continental base of northern Qaidam,suggesting that the base rocks have provided materials for the formation of sedimentary and volcanic rock in O2-3tnd.The volcanic rocks of O3tnd-3formed at 440 Ma,with time gap 46 Ma to those of O1tna-1and O3tnd-3may represent the minor period that Xitieshan back-arc extension have lasted,the scale of back-arc basin that formed in Xitieshan extension may approach to 1 400 km.Based on the test of ithochemistry data for major elements and analysis of Sr isotope geochemistry for the clastic sedimentary rock in O1tna-2and O3tnd-2,the authors get the conclusion that the O1tna-2and O3tnd-2of Tanjianshan Group may form in back-arc basin environment,while the lithology difference between these two formations may reflect the changes of geodynamic processes as the diagenesis tectonic environment transformed from continental margin depression to adjacent sea basin. | ZHANG Shanming SUN Huashan ZHU Zhexin LIU Hongwei CHI Hongxin | 2013 | Global Geology2013，16，3： | 0 |
| 3 | End-to-end spatial transform face detection and recognition显示文摘Background Several face detection and recogni tion methods have been proposed in the past decades that have excellent performance.The conventional face recognition pipeline comprises the following:(1)face detection,(2)face alignment,(3)feature extraction,and(4)similarity,which are independent of each other.The separate facial analysis stages lead to redundant model calculations,and are difficult for use in end-to-end training.Methods In this paper,we propose a novel end-to-end trainable convolutional network framework for face detection and recognition,in which a geometric transformation matrix is directly learned to align the faces rather than predicting the facial landmarks.In the training stage,our single CNN model is supervised only by face bounding boxes and personal identities,which are publicly available from WIDER FACE and CASIA-WebFace datasets.Our model is tested on Face Detection Dataset and Benchmark(FDDB)and Labeled Face in the Wild(LFW)datasets.Results The results show 89.24%recall for face detection tasks and 98.63%accura cy for face recognition tasks. | Hongxin ZHANG Liying CHI | 2020 | Virtual Reality & Intelligent Hardware2020，2，2： | 0 |
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