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Learning a Deep Predictive Coding Network for a Semi-Supervised 3D-Hand Pose Estimation

IEEE/CAA Journal of Automatica Sinica 2020年第5期7卷 1371-1379页

作者： Jamal Banzi Isack Bulugu zhongfu ye Sokoine University Morogoro 3000Tanzania University of Dar-es-Salaam Dar-es-Salaam 35091Tanzania Department of Electronic Engineering and Information Science University of Science and Technology of ChinaHefei 230026China IEEE

In this paper we present a CNN based approach for a real time 3 D-hand pose estimation from the depth sequence.Prior discriminative approaches have achieved remarkable success but are facing two main challenges:Firstly,the methods are fully supervised hence require large numbers of annotated training data to extract the dynamic information from a hand representation.Secondly,unreliable hand detectors based on strong assumptions or a weak detector which often fail in several situations like complex environment and multiple hands.In contrast to these methods,this paper presents an approach that can be considered as semi-supervised by performing predictive coding of image sequences of hand poses in order to capture latent features underlying a given image without supervision.The hand is modelled using a novel latent tree dependency model(LDTM)which transforms internal joint location to an explicit representation.Then the modeled hand topology is integrated with the pose estimator using data dependent method to jointly learn latent variables of the posterior pose appearance and the pose configuration respectively.Finally,an unsupervised error term which is a part of the recurrent architecture ensures smooth estimations of the final pose.Experiments on three challenging public datasets,ICVL,MSRA,and NYU demonstrate the significant performance of the proposed method which is comparable or better than state-of-the-art approaches.

关键词： Convolutional neural networks deep learning hand pose estimation human-machine interaction predictive coding recurrent neural networks unsupervised learning

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Learning Hand Latent Features for Unsupervised 3D Hand Pose Estimation

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Journal of Autonomous Intelligence 2019年第1期2卷 1-10页

作者： Jamal Banzi Isack Bulugu zhongfu ye School of Information Science and Technology University of Science and Technology of China230026China Sokoine University of Agriculture Morogoro3167Tanzania College of information and communication Technology University of Dare-es-salaamDar-es-Salaam33335Tanzania

Recent hand pose estimation methods require large numbers of annotated training data to extract the dynamic information from a hand representation.Nevertheless,precise and dense annotation on the real data is difficult to come by and the amount of information passed to the training algorithm is significantly higher.This paper presents an approach to developing a hand pose estimation system which can accurately regress a 3D pose in an unsupervised manner.The whole process is performed in three stages.Firstly,the hand is modelled by a novel latent tree dependency model (LTDM) which transforms internal joints location to an explicit representation.Secondly,we perform predictive coding of image sequences of hand poses in order to capture latent features underlying a given image without supervision.A mapping is then performed between an image depth and a generated representation.Thirdly,the hand joints are regressed using convolutional neural networks to finally estimate the latent pose given some depth map.Finally,an unsupervised error term which is a part of the recurrent architecture ensures smooth estimation of the final pose.To demonstrate the performance of the proposed system,a complete experiment was conducted on three challenging public datasets,ICVL,MSRA,and NYU.The empirical results show the significant performance of our method which is comparable or better than the state-of-the-art approaches.

关键词： Hand Pose Estimation Convolutional Neural Networks Recurrent Neural Networks Human-machine Interaction Predictive Coding Unsupervised Learning

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A Novel Intelligent System for Dynamic Observation of Cotton Verticillium Wilt

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Plant Phenomics 2023年第1期5卷 73-84页

作者： Chenglong Huang zhongfu Zhang Xiaojun Zhang Li Jiang Xiangdong Hua Junli ye Wanneng Yang Peng Song Longfu Zhu College of Engineering Huazhong Agricultural UniversityWuhan 430070PR China College of Plant Science&Technology Huazhong Agricultural UniversityWuhan 430070PR China National Key Laboratory of Crop Genetic Improvement National Center of Plant Gene Research(Wuhan)Huazhong Agricultural UniversityWuhan 430070PR China

Verticillium wilt is one of the most critical cotton diseases,which is widely distributed in cotton-producing countries.However,the conventional method of verticillium wilt investigation is still manual,which has the disadvantages of subjectivity and low efficiency.In this research,an intelligent vision-based system was proposed to dynamically observe cotton verticillium wilt with high accuracy and high throughput.Firstly,a 3-coordinate motion platform was designed with the movement range 6,100 mm×950 mm×500 mm,and a specific control unit was adopted to achieve accurate movement and automatic imaging.Secondly,the verticillium wilt recognition was established based on 6 deep learning models,in which the VarifocalNet(VFNet)model had the best performance with a mean average precision(mAP)of 0.932.Meanwhile,deformable convolution,deformable region of interest pooling,and soft non-maximum suppression optimization methods were adopted to improve VFNet,and the mAP of the VFNet-Improved model improved by 1.8%.The precision–recall curves showed that VFNet-Improved was superior to VFNet for each category and had a better improvement effect on the ill leaf category than fine leaf.The regression results showed that the system measurement based on VFNet-Improved achieved high consistency with manual measurements.Finally,the user software was designed based on VFNet-Improved,and the dynamic observation results proved that this system was able to accurately investigate cotton verticillium wilt and quantify the prevalence rate of different resistant varieties.In conclusion,this study has demonstrated a novel intelligent system for the dynamic observation of cotton verticillium wilt on the seedbed,which provides a feasible and effective tool for cotton breeding and disease resistance research.

关键词： system category cotton

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激光技术在金刚石加工中的研究及应用进展

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红外与激光工程 2024年第2期53卷 36-57页

作者：叶盛赵上熳邢忠福彭志勇郑宇亭陈良贤刘金龙李成明魏俊俊北京科技大学新材料技术研究院北京100083 天津津航技术物理研究所天津300308 北京科技大学顺德创新学院广东佛山528399

激光加工是目前金刚石的主流加工方法,相较于传统的机械加工形式,激光加工精度高、效率高、普适性强,因而在金刚石切割、微孔成型、微槽道加工及平整化等方面均得到广泛应用。文中阐述了金刚石激光加工原理,介绍了不同类型激光与金刚石... 详细信息

激光加工是目前金刚石的主流加工方法,相较于传统的机械加工形式,激光加工精度高、效率高、普适性强,因而在金刚石切割、微孔成型、微槽道加工及平整化等方面均得到广泛应用。文中阐述了金刚石激光加工原理,介绍了不同类型激光与金刚石材料相互作用机制,重点总结了近几年多种激光加工金刚石模式的发展现状,分析了新型的激光加工方法的特点,探讨了现阶段激光技术在金刚石加工领域面临的问题、挑战及未来的发展趋势。

关键词：金刚石激光加工激光切割微孔成型微槽道激光平整化

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Blind channel identication of nonlinear folding mixing model

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Journal of Systems Engineering and Electronics 2006年第3期17卷 509-512页

作者： Su Yong Xu Shangzhi ye zhongfu Inst. of Statistical Signal Processing Dept. of Electronic Engineering and Information Science Univ. of Science and Technology of China Hefei 230027 P. R. China

Signals from multi-sensor systems are often mixtures of （statistically） independent sources by unknown mixing method. Blind source separation（BSS） and independent component analysis（ICA） are the methods to identify/recover the channels and the sources. BSS/ICA of nonlinear mixing models are difficult problems. For instance, the post-nonlinear model has been studied by several authors. It is noticed that in most cases, the proposed models are always with an invertible mixing. According to this fact there is an interesting question, how about the situation of the non-invertible non-linear mixing in BSS or ICA？ A new simple non-linear mixing model is proposed with a kind of non-invertible mixing, the folding mixing, and method to identify its channel, blindly.

关键词： blind channel identication non-linear mixing non-invertible.

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Supervised Analysis of Hepatitis C Virus RNA-Positive Case Reporting in County-Level Hospitals--China,2013−2018

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China CDC weekly 2020年第31期2卷 587-590页

作者： Faxin Hei Guowei Ding Shaodong ye Hailiang Yu Lin Pang zhongfu Liu National Center for STD/AIDS Prevention and Control Chinese Center for Disease Control and PreventionBeijingChina

What is already known on this topic?To understand the status of the diagnosis and reporting of hepatitis C and standardize the reporting of hepatitis C cases in county-level hospitals,we conducted the first supervised analysis of hepatitis C cases in county-level hospitals in China from 2013 to 2018,covering all provincial-level administrative divisions(PLADs)except Tibet.What is added by this report?Through 6 years of supervision,we have obtained key data such as the nucleic acid detection rate and positive rate of hepatitis C virus(HCV)antibody positive cases in our county-level hospitals,the report rate and accuracy of HCV RNA positive cases,and standardized and improved the hepatitis C case reporting in countylevel hospitals to improve data quality and provide data support for the judgment and estimation of hepatitis C in China.What are the implications for public health practice?By strengthening the management and supervision of hepatitis C case reporting,the reporting rate and accuracy of HCV RNA positive cases in county-level hospitals in China had been greatly improved.By combining the number of HCV antibody tests and the number of viral nucleic acid tests in medical institutions around the country,it was possible to effectively assess the current status of hepatitis C in China and to provide a scientific basis for the development of hepatitis C prevention and treatment measures.

关键词： prevention diagnosis strengthening

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基于KASP标记快速鉴定瓠瓜杂种F_(1)纯度的方法

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分子植物育种 2024年第9期22卷 2947-2951页

作者：冯子珊吴晓花李艳伟鲁忠富王尖吴新义汪宝根叶子弘李国景汪颖中国计量大学生命科学学院杭州310018 浙江省农业科学院蔬菜研究所杭州310021

瓠瓜为中国南方重要特色瓜类蔬菜之一,随着瓠瓜育成品种数量逐年增多,同名异种、同种异名引发的知识产权纠纷多见。传统上对品种的鉴定主要依靠田间种植,效率低。本研究以浙江省农业科学院蔬菜所新育成的高品质短棒瓠瓜杂交种‘浙蒲9号... 详细信息

瓠瓜为中国南方重要特色瓜类蔬菜之一,随着瓠瓜育成品种数量逐年增多,同名异种、同种异名引发的知识产权纠纷多见。传统上对品种的鉴定主要依靠田间种植,效率低。本研究以浙江省农业科学院蔬菜所新育成的高品质短棒瓠瓜杂交种‘浙蒲9号’及其亲本为试材,选取了3对‘浙蒲9号’亲本特异性SNP引物,基于LGC KASP高通量技术平台,对‘浙蒲9号’父本、母本以及92份F_(1)材料进行鉴定,结果显示‘浙蒲9号’F_(1)种子纯度为97.8%,与田间种植纯度鉴定结果一致。该方法准确性好、成本低且高效,单孔不超过1元,检测全程仅需5 d左右,大大缩短了品种鉴定的时间,是一种准确、简便、快速的瓠瓜品种鉴定和纯度检测方法,应用前景非常广泛。

关键词：瓠瓜 KASP标记纯度鉴定快速浙蒲9号

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Improvement of joint optimization of masks and deep recurrent neural networks for monaural speech separation using optimized activation functions

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Chinese Journal of Acoustics 2020年第3期39卷 420-432页

作者： MASOOD Asim ye zhongfu National Engineering Laboratory for Speech and Language Information Processing University of Science and Technology of ChinaHefei 230026

Single channel speech separation was a challenging task for speech separation community for last three decades.It is now possible to separate speeches using deep neural networks(DNN)and deep recurrent neural networks(DRNN)due to deep learning.Researchers are now trying to improve different models of DNN and DRNN for monaural speech separation.In this paper,we have tried to improve existing DRNN and DNN based model for speech separation by using optimized activation functions.Instead of using rectified linear unit(RELU),we have implemented leaky RELU,exponential linear unit,exponential function,inverse square root linear unit and inverse cubic root linear unit(ICRLU)as activation functions.ICRLU and exponential function are new activation functions proposed in this research work.These activation functions have overcome the dying RELU problem.They have achieved better separation results in comparison with RELU function and they have also reduced the computational cost of DNN and DRNN based monaural speech separation.

关键词： separation activation functions

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Color-tunable ultralong organic phosphorescence materials for visual UV-light detection

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Science China Chemistry 2020年第10期63卷 1443-1448页

作者： Lifang Bian Huili Ma Wenpeng ye Anqi Lv He Wang Wenyong Jia Long Gu Huifang Shi zhongfu An Wei Huang Key Laboratory of Flexible Electronics(KLOFE)&Institute of Advanced Materials(IAM) Nanjing Tech UniversityNanjing 211816China 2Frontiers Science Center for Flexible Electronics(FSCFE) Shaanxi Institute of Flexible Electronics(SIFE)&Shaanxi Institute of Biomedical Materials and Engineering(S/BME)Northwestern Polytechnical University(NPU)Xi'an 710072China

Ultralong organic phosphorescence(UOP)materials have roused considerable attention in the field of photonics and optoelectronics owing to the feature of long-lived emission lifetimes.However,to develop UOP materials with color-tunability is still a formidable challenge.Here,we report a class of UOP materials containing carbonyl,amino or amide groups,exhibiting colortunable persistent luminescence ranging from blue(458 nm)to yellow-green(508 nm)under different UV wavelength excitation.Taken theoretical and experimental results together,we conclude that the excitation dependent color-tunable UOP emission is ascribed to multiple emission centers from single molecular and aggregated states in crystal.Given color-tunable UOP feature,these materials are used to successfully realize visual UV-light detection.This finding not only provides a strategy to design new organic phosphorescent molecules with colorful emission,but also extends the scope of the applications of purely organic phosphorescent materials.

关键词： color tunability room temperature phosphorescence excitation dependent emission persistent luminescence UV-light detection

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A universal pipeline for mobile mRNA detection and insights into heterografting advantages under chilling stress

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Horticulture Research 2020年第1期7卷 2575-2584页

作者： Ying Wang Lingping Wang Nailin Xing Xiaohua Wu Xinyi Wu Baogen Wang zhongfu Lu Pei Xu ye Tao Guojing Li Yuhong Wang Institute of Vegetables Zhejiang Academy of Agricultural SciencesHangzhou 310021China Institute of Vegetables Ningbo Academy of Agricultural SciencesNingbo 315040China State Key Laboratory for Quality and Safety of Agroproducts Zhejiang Academy of Agricultural SciencesHangzhou 310021China Biozeron Biotechnology Co. Ltd.Shanghai 201800China Present address:College of Life Sciences China Jiliang UniversityHangzhou 310018China

Heterografting has long been used to enhance the chilling tolerance of temperature-sensitive crops,including watermelon,whose mechanism is known to involve bidirectional long-distance mRNA movements.Despite several studies reporting on mobile mRNA(mb-mRNA)profiles in plants,accurate identification of mb-mRNAs is challenging owing to an array of technical problems.Here,we developed a bioinformatical pipeline that took most of the known technical concerns into consideration and is considered to be a universal tool for mb-mRNA detection in heterografts.By applying this pipeline to a commercial watermelon–bottle gourd heterografting system,we detected 130 and 1144 mb-mRNAs upwardly and 167 and 1051 mb-mRNAs downwardly transmitted under normal and chilling-stress conditions,respectively.Quantitative real-time PCR indicated a high accuracy rate(88.2%)of mb-mRNA prediction with our pipeline.We further revealed that the mobility of mRNAs was not associated with their abundance.Functional annotation and classification implied that scions may convey the stress signal to the rootstock,subsequently triggering energy metabolism reprogramming and abscisic acid-mediated stress responses by upward movement of effective mRNAs,ultimately leading to enhanced chilling tolerance.This study provides a universal tool for mb-mRNA detection in plant heterografting systems and novel insights into heterografting advantages under chilling stress.

关键词： metabolism grafting stress

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