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| 1 | Preprocessing method of night vision image application in apple harvesting robot显示文摘Due to the low working efficiency of apple harvesting robots,there is still a long way to go for commercialization.The machine performance and extended operating time are the two research aspects for improving efficiencies of harvesting robots,this study focused on the extended operating time and proposed a round-the-clock operation mode.Due to the influences of light,temperature,humidity,etc.,the working environment at night is relatively complex,and thus restricts the operating efficiency of the apple harvesting robot.Three different artificial light sources(incandescent lamp,fluorescent lamp,and LED lights)were selected for auxiliary light according to certain rules so that the apple night vision images could be captured.In addition,by color analysis,night and natural light images were compared to find out the color characteristics of the night vision images,and intuitive visual and difference image methods were used to analyze the noise characteristics.The results showed that the incandescent lamp is the best artificial auxiliary light for apple harvesting robots working at night,and the type of noise contained in apple night vision images is Gaussian noise mixed with some salt and pepper noise.The preprocessing method can provide a theoretical and technical reference for subsequent image processing. | Weikuan Jia Yuanjie Zheng De’an Zhao Xiang Yin Xiaoyang Liu Ruicheng Du | 2018 | International Journal of Agricultural and Biological Engineering2018，11，2： | 2 |
| 2 | Exploiting GSM shor message service for ubiquitous accessing显示文摘 | Tang MingChung Chou ChunNun Tang ChingHui Pan D C Shih WeiKuan | 2001 | Journal of Network and Computer Applications2001，24，： | 1 |
| 3 | Research on using genetic algorithms to optimize Elman neural networks显示文摘 | Shifei Ding Yanan Zhang Jinrong Chen Weikuan Jia | 2013 | Neural Computing and Applications2013，，2： | 1 |
| 4 | Dual Effects of IL-1 Overactivity on the Immune System in a Mouse Model of Arthritis due to Deficiency of IL-1 Receptor Antagonist显示文摘Previous studies have revealed the significance of cytokine interleukin 1(IL-1) in the onset and progression of rheumatoid arthritis (RA).The precise molecular mechanisms related to IL-1 underlying RA is still elusive.We conducted a whole genome-wide transcriptomal comparison of wild-type(WT) and arthritis-prone IL-1 receptor antagonist(IL-1rn) deficient BALB/c mice to address this issue.To refine our search efforts,gene expression profiling was also performed on paired wild-type and arthritis-resistant IL-lm deficient DBA/1 mice as internal controls when identifying causative arthritis candidate genes.Two hundred and fifteen transcripts were found to be dysregulated greater than or equal to 2-fold in the diseased mice.The altered transcriptome in BALB/c mice revealed increased myeloid cell activities and impaired lymphocyte functionality,suggesting dual regulatory effects of IL-1 hyperactivity on immunological changes associated with arthritis development.Phase-specific gene expression changes were identified,such as early increase and late decrease of heat shock protein coding genes.Moreover,common gene expression changes were also observed,especially the upregulation of paired Ig-like receptor A(Pira) in both early and late phases of arthritis.Real-time PCR was performed to validate the expression of Pira and an intervention experiment with a major histocompatibility complex(MHC) class I inhibitor(brefeldin A) was carried out to investigate the role of suppressing Pira activity.We conclude that global pattern changes of common and distinct gene expressions may represent novel opportunities for better control of RA through early diagnosis and development of alternative therapeutic strategies. | Jian Yan Yan Jiao Hong Chen Feng Jiao Karen A.Hasty John M.Stuart Weikuan Gu | 2013 | Journal of Genetics and Genomics2013，40，2： | 1 |
| 5 | Application of ultrasonic irradiation in preparing conducting polymer as active materials for supercapacitor显示文摘 | Li Weikuan Chen Juan Zhao Junjun | 2005 | Mater Lett2005，59，： | 1 |
| 6 | Security enhancement on an improvement on two remote user authentication schemes using smart cards显示文摘 | CHEN Tien-Ho HSIANG Han-Cheng SHIH Weikuan | 2011 | Fu- ture Generation Computer Systems2011，27，4： | 1 |
| 7 | Genetic control of the rate of wound healing in mice显示文摘 | X Li Weikuan GU and Godfred M | 2001 | Heredity2001，86，6： | 1 |
| 8 | A robust mutual authentication protocol for wireless sensor networks 显示文摘 | Chen Tienho Shih Weikuan | 2010 | Electronics and Telecommunications Research Institute Journal2010，32，5： | 1 |
| 9 | BFP Net: Balanced Feature Pyramid Network for Small Apple Detection in Complex Orchard Environment显示文摘Despite of significant achievements made in the detection of target fruits,small fruit detection remains a great challenge,especially for immature small green fruits with a few pixels.The closeness of color between the fruit skin and the background greatly increases the difficulty of locating small target fruits in the natural orchard environment.In this paper,we propose a balanced feature pyramid network(BFP Net)for small apple detection. | Meili Sun Liancheng Xu Xiude Chen Ze Ji Yuanjie Zheng Weikuan Jia | 2022 | Plant Phenomics2022，4，1： | 1 |
| 10 | Ad Hoc File Systems for High-Performance Computing显示文摘Storage backends of parallel compute clusters are still based mostly on magnetic disks,while newer and faster storage technologies such as flash-based SSDs or non-volatile random access memory(NVRAM)are deployed within compute nodes.Including these new storage technologies into scientific workflows is unfortunately today a mostly manual task,and most scientists therefore do not take advantage of the faster storage media.One approach to systematically include nodelocal SSDs or NVRAMs into scientific workflows is to deploy ad hoc file systems over a set of compute nodes,which serve as temporary storage systems for single applications or longer-running campaigns.This paper presents results from the Dagstuhl Seminar 17202'Challenges and Opportunities of User-Level File Systems for HPC'and discusses application scenarios as well as design strategies for ad hoc file systems using node-local storage media.The discussion includes open research questions,such as how to couple ad hoc file systems with the batch scheduling environment and how to schedule stage-in and stage-out processes of data between the storage backend and the ad hoc file systems.Also presented are strategies to build ad hoc file systems by using reusable components for networking and how to improve storage device compatibility.Various interfaces and semantics are presented,for example those used by the three ad hoc file systems BeeOND,GekkoFS,and BurstFS.Their presentation covers a range from file systems running in production to cutting-edge research focusing on reaching the performance limits of the underlying devices. | AndréBrinkmann Kathryn Mohror Weikuan Yu Philip Carns Toni Cortes Scott A.Klasky Alberto Miranda Franz-Josef Pfreundt Robert B.Ross Marc-AndréVef | 2020 | Journal of Computer Science & Technology2020，35，1： | 0 |
| 11 | Preface显示文摘It is our great pleasure to announce the publication of this special section in JCST,Selected I/O Technologies for High-Performance Computing and Data Analytics.With the explosive grow th of colossal data from various academic and industrial sectors,many High-Performance Computing(HPC)and data analytics systems have been developed to meet the needs of data collection,processing and analysis.Accordingly,many research groups around the world have explored unconventional and cut ting-edge ideas for the management of storage and I/O. | Xian-He Sun Weikuan Yu | 2020 | Journal of Computer Science & Technology2020，35，1： | 0 |
| 12 | Novel green-fruit detection algorithm based on D2D framework显示文摘In the complex orchard environment,the efficient and accurate detection of object fruit is the basic requirement to realize the orchard yield measurement and automatic harvesting.Sometimes it is hard to differentiate between the object fruits and the background because of the similar color,and it is challenging due to the ambient light and camera angle by which the photos have been taken.These problems make it hard to detect green fruits in orchard environments.In this study,a two-stage dense to detection framework(D2D)was proposed to detect green fruits in orchard environments.The proposed model was based on multi-scale feature extraction of target fruit by using feature pyramid networks MobileNetV2+FPN structure and generated region proposal of target fruit by using Region Proposal Network(RPN)structure.In the regression branch,the offset of each local feature was calculated,and the positive and negative samples of the region proposals were predicted by a binary mask prediction to reduce the interference of the background to the prediction box.In the classification branch,features were extracted from each sub-region of the region proposal,and features with distinguishing information were obtained through adaptive weighted pooling to achieve accurate classification.The new proposed model adopted an anchor-free frame design,which improves the generalization ability,makes the model more robust,and reduces the storage requirements.The experimental results of persimmon and green apple datasets show that the new model has the best detection performance,which can provide theoretical reference for other green object detection. | Jinmeng Wei Yanhui Ding Jie Liu Muhammad Zakir Ullah Xiang Yin Weikuan Jia | 2022 | International Journal of Agricultural and Biological Engineering2022，15，1： | 0 |
| 13 | SE-COTR: A Novel Fruit Segmentation Model for Green Apples Application in Complex Orchard显示文摘Because of the unstructured characteristics of natural orchards,the efficient detection and segmentation applications of green fruits remain an essential challenge for intelligent agriculture.Therefore,an innovative fruit segmentation method based on deep learning,termed SE-COTR(segmentation based on coordinate transformer),is proposed to achieve accurate and real-time segmentation of green apples. | Zhifen Wang Zhonghua Zhang Yuqi Lu Rong Luo Yi Niu Xinbo Yang Shaoxue Jing Chengzhi Ruan Yuanjie Zheng Weikuan Jia | 2022 | Plant Phenomics2022，4，1： | 0 |
| 14 | Joint Deep Matching Model of OCT Retinal Layer Segmentation显示文摘Optical Coherence Tomography(OCT)is very important in medicine and provide useful diagnostic information.Measuring retinal layer thicknesses plays a vital role in pathophysiologic factors of many ocular conditions.Among the existing retinal layer segmentation approaches,learning or deep learning-based methods belong to the state-of-art.However,most of these techniques rely on manual-marked layers and the performances are limited due to the image quality.In order to overcome this limitation,we build a framework based on gray value curve matching,which uses depth learning to match the curve for semi-automatic segmentation of retinal layers from OCT.The depth convolution network learns the column correspondence in the OCT image unsupervised.The whole OCT image participates in the depth convolution neural network operation,compares the gray value of each column,and matches the gray value sequence of the transformation column and the next column.Using this algorithm,when a boundary point is manually specified,we can accurately segment the boundary between retinal layers.Our experimental results obtained from a 54-subjects database of both normal healthy eyes and affected eyes demonstrate the superior performances of our approach. | Mei Yang Yuanjie Zheng Weikuan Jia Yunlong He Tongtong Che Jinyu Cong | 2020 | Computers, Materials & Continua2020，，6： | 0 |
| 15 | 10G以太网与无限宽频技术的广域性能对比显示文摘对于广域高性能应用程序来说,轻路径提供了10Gbps的连接,并且拥有PIC—E接口的多核主机可以达到这样的速率。然而要在远隔上千英里的主机之间维持这样的高吞吐率是一个很大的挑战,而且目前这方面的性能研究还很有限。我们对两种基于不同技术达到高吞吐率的方案进行了试验研究:(a)基于TCP/IP协议的10Gbps以太网;(b)无限宽频及其扩展。 | Negeswara S.V Weikuan Yu | 2009 | 中国教育网络2009，，1： | 0 |
| 16 | ASRNet: Adversarial Segmentation and Registration Networks for Multispectral Fundus Images显示文摘Multispectral imaging (MSI) technique is often used to capture imagesof the fundus by illuminating it with different wavelengths of light. However,these images are taken at different points in time such that eyeball movementscan cause misalignment between consecutive images. The multispectral imagesequence reveals important information in the form of retinal and choroidal bloodvessel maps, which can help ophthalmologists to analyze the morphology of theseblood vessels in detail. This in turn can lead to a high diagnostic accuracy of several diseases. In this paper, we propose a novel semi-supervised end-to-end deeplearning framework called “Adversarial Segmentation and Registration Nets”(ASRNet) for the simultaneous estimation of the blood vessel segmentation andthe registration of multispectral images via an adversarial learning process. ASRNet consists of two subnetworks: (i) A segmentation module S that fulfills theblood vessel segmentation task, and (ii) A registration module R that estimatesthe spatial correspondence of an image pair. Based on the segmention-drivenregistration network, we train the segmentation network using a semi-supervisedadversarial learning strategy. Our experimental results show that the proposedASRNet can achieve state-of-the-art accuracy in segmentation and registrationtasks performed with real MSI datasets. | Yanyun Jiang Yuanjie Zheng Xiaodan Sui Wanzhen Jiao Yunlong He Weikuan Jia | 2021 | Computer Systems Science & Engineering2021，36，3： | 0 |
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