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3D Object Tracking with Transformer [article]

Yubo Cui, Zheng Fang, Jiayao Shan, Zuoxu Gu, Sifan Zhou
2021 arXiv   pre-print
Feature fusion and similarity computation are two core problems in 3D object tracking, especially for object tracking using sparse and disordered point clouds. Feature fusion could make similarity computing more efficient by including target object information. However, most existing LiDAR-based approaches directly use the extracted point cloud feature to compute similarity while ignoring the attention changes of object regions during tracking. In this paper, we propose a feature fusion network
more » ... based on transformer architecture. Benefiting from the self-attention mechanism, the transformer encoder captures the inter- and intra- relations among different regions of the point cloud. By using cross-attention, the transformer decoder fuses features and includes more target cues into the current point cloud feature to compute the region attentions, which makes the similarity computing more efficient. Based on this feature fusion network, we propose an end-to-end point cloud object tracking framework, a simple yet effective method for 3D object tracking using point clouds. Comprehensive experimental results on the KITTI dataset show that our method achieves new state-of-the-art performance. Code is available at:
arXiv:2110.14921v1 fatcat:sb3m7tjucrcwdjhdjqsj2d4t4y

A Real-Time and Multi-Sensor-Based Landing Area Recognition System for UAVs

Fei Liu, Jiayao Shan, Binyu Xiong, Zheng Fang
2022 Drones  
This paper presents a real-time and multi-sensor-based landing area recognition system for UAVs, which aims to enable UAVs to land safely on open and flat terrain and is suitable for comprehensive unmanned autonomous operation. The landing area recognition system for UAVs is built on the combination of a camera and a 3D LiDAR. The problem is how to fuse the image and point cloud information and realize the landing area recognition to guide the UAV landing autonomously and safely. To solve this
more » ... roblem, firstly, we use a deep learning method to realize the landing area recognition and tracking from images. After that, we project 3D LiDAR point cloud data into camera coordinates to obtain the semantic label of each point. Finally, we use the 3D LiDAR point cloud data with the semantic label to build the 3D environment map and calculate the most suitable area for UAV landing. Experiments show that the proposed method can achieve accurate and robust recognition of landing area for UAVs.
doi:10.3390/drones6050118 fatcat:c3bfbzvoxzcr5mze5powbmkcui

Ciphertext-only fault analysis on the Midori lightweight cryptosystem

Wei Li, Linfeng Liao, Dawu Gu, Shan Cao, Yixin Wu, Jiayao Li, Zhihong Zhou, Zheng Guo, Ya Liu, Zhiqiang Liu
2020 Science China Information Sciences  
doi:10.1007/s11432-018-9522-6 fatcat:cp76gv757jhhniwn67hzycgkvi

Regional biomechanical imaging of liver cancer cells

Weiwei Pei, Jiayao Chen, Chao Wang, Suhao Qiu, Jianfeng Zeng, Mingyuan Gao, Bin Zhou, Dan Li, Michael S. Sacks, Lin Han, Hong Shan, Wentao Hu (+2 others)
2019 Journal of Cancer  
Liver cancer is one of the leading cancers, especially in developing countries. Understanding the biomechanical properties of the liver cancer cells can not only help to elucidate the mechanisms behind the cancer progression, but also provide important information for diagnosis and treatment. At the cellular level, we used well-established atomic force microscopy (AFM) techniques to characterize the heterogeneity of mechanical properties of two different types of human liver cancer cells and a
more » ... ormal liver cell line. Stiffness maps with a resolution of 128x128 were acquired for each cell. The distributions of the indentation moduli of the cells showed significant differences between cancerous cells and healthy controls. Significantly, the variability was even greater amongst different types of cancerous cells. Fitting of the histogram of the effective moduli using a normal distribution function showed the Bel7402 cells were stiffer than the normal cells while HepG2 cells were softer. Morphological analysis of the cell structures also showed a higher cytoskeleton content among the cancerous cells. Results provided a foundation for applying knowledge of cell stiffness heterogeneity to search for tissue-level, early-stage indicators of liver cancer.
doi:10.7150/jca.32985 pmid:31528212 pmcid:PMC6746127 fatcat:nb3rqifivzbvdj5jpvpnijmtxy

The role of the tumor microbe microenvironment in the tumor immune microenvironment: bystander, activator, or inhibitor?

Jiayao Ma, Lingjuan Huang, Die Hu, Shan Zeng, Ying Han, Hong Shen
2021 Journal of Experimental & Clinical Cancer Research  
AbstractThe efficacy of cancer immunotherapy largely depends on the tumor microenvironment, especially the tumor immune microenvironment. Emerging studies have claimed that microbes reside within tumor cells and immune cells, suggesting that these microbes can impact the state of the tumor immune microenvironment. For the first time, this review delineates the landscape of intra-tumoral microbes and their products, herein defined as the tumor microbe microenvironment. The role of the tumor
more » ... be microenvironment in the tumor immune microenvironment is multifaceted: either as an immune activator, inhibitor, or bystander. The underlying mechanisms include: (I) the presentation of microbial antigens by cancer cells and immune cells, (II) microbial antigens mimicry shared with tumor antigens, (III) microbe-induced immunogenic cell death, (IV) microbial adjuvanticity mediated by pattern recognition receptors, (V) microbe-derived metabolites, and (VI) microbial stimulation of inhibitory checkpoints. The review further suggests the use of potential modulation strategies of the tumor microbe microenvironment to enhance the efficacy and reduce the adverse effects of checkpoint inhibitors. Lastly, the review highlights some critical questions awaiting to be answered in this field and provides possible solutions. Overall, the tumor microbe microenvironment modulates the tumor immune microenvironment, making it a potential target for improving immunotherapy. It is a novel field facing major challenges and deserves further exploration.
doi:10.1186/s13046-021-02128-w pmid:34656142 pmcid:PMC8520212 fatcat:fq6zj7lhu5fmtkduagu44ifiu4

PTT: Point-Track-Transformer Module for 3D Single Object Tracking in Point Clouds [article]

Jiayao Shan, Sifan Zhou, Zheng Fang, Yubo Cui
2021 arXiv   pre-print
3D single object tracking is a key issue for robotics. In this paper, we propose a transformer module called Point-Track-Transformer (PTT) for point cloud-based 3D single object tracking. PTT module contains three blocks for feature embedding, position encoding, and self-attention feature computation. Feature embedding aims to place features closer in the embedding space if they have similar semantic information. Position encoding is used to encode coordinates of point clouds into high
more » ... distinguishable features. Self-attention generates refined attention features by computing attention weights. Besides, we embed the PTT module into the open-source state-of-the-art method P2B to construct PTT-Net. Experiments on the KITTI dataset reveal that our PTT-Net surpasses the state-of-the-art by a noticeable margin (~10%). Additionally, PTT-Net could achieve real-time performance (~40FPS) on NVIDIA 1080Ti GPU. Our code is open-sourced for the robotics community at
arXiv:2108.06455v3 fatcat:oebwissvifg4znge67cd7jdjlq

A Study of Hu Shi's Scholarship on the Platform Sutra

2018 DEStech Transactions on Social Science Education and Human Science  
Version of the Platform Sutra"(Duhuang xieben liuzu tanjing de faxian yu wenzi jiaoding fangfa) [12] 2007 Pan Guiming "Research on Hu Shi's view of Chan Buddhist Historical Studies" [13] 1998 Yuan Jiayao  ...  follows, (1) Dunhuang Library version of the Dunhuang Platform Sutra (D. 077-4): This version was found by Ren Ziyu (1915-1988) in Zhishang Temple (zhishang si) of Dunhuang Thousand Buddha Mountain (qianfo shan  ... 
doi:10.12783/dtssehs/ichss2017/19568 fatcat:lljciiyqjva6nfgts34vrozmem

Front Matter [chapter]

International Conference on Computer and Electrical Engineering 4th (ICCEE 2011)  
doi:10.1115/ fatcat:qzorxwwjvjechd3a7wllknhr4q

Acknowledgment to Reviewers of Sustainability in 2020

Sustainability Editorial Office Sustainability Editorial Office
2021 Sustainability  
Hu, Tai-Shan Hosono, Kaoru Hu, Wanhe Hossain, AKM Nurul Hu, Yimei Hossain, Eklas Hua, Jie Hossain, Md.  ...  Severin Hsu, Tai-Wen Horobet, Alexandra Hsu, Yu Lun Horodnic, Ioana Alexandra Hsu, Yu-Charn Horská, Elena Hu, Bifeng Horswill, Craig A Hu, Chich-Ping Horszczaruk, Elżbieta Hu, Guangji Horta, Carmo Hu, Jiayao  ... 
doi:10.3390/su13031299 fatcat:ag24ixgny5dofgfsmzpkuanptq

Interactions Between Microplastics and Heavy Metals in Aquatic Environments: A Review

Sitong Liu, Jiafu Shi, Jiao Wang, Yexin Dai, Hongyu Li, Jiayao Li, Xianhua Liu, Xiaochen Chen, Zhiyun Wang, Pingping Zhang
2021 Frontiers in Microbiology  
., 2020; Shan et al., 2020) .  ... 
doi:10.3389/fmicb.2021.652520 pmid:33967988 pmcid:PMC8100347 fatcat:bosbruyz2bbttknj3kmtei2rom

Among the New Books

N. James, Stephanie Wynne-Jones
2004 Antiquity  
Early Beth Shan (Strata XIX-XIII): G.M. FitzGerald's Deep Cut on the Tell (University Museum Monograph 121). xiv+194 pages, 114 figures, 23 tables. 2004.  ...  WATT, AN JIAYAO, ANGELA F. HOWARD, BORIS I. MARSHAK, SU BAI, ZHAO FENG, PRUDENCE O. HARPER, MAXWELL K. HEARN, DENISE PATRY LEIDY, CHAO-HUI JENNY LIU, VALENTINA RASPOPOVA & ZHIXIN SUN (tr.  ... 
doi:10.1017/s0003598x00113638 fatcat:ssawnfzcpbbufdhoovazuqwzka

Author Index

2021 2021 40th Chinese Control Conference (CCC)   unpublished
MIAO Chunxiao . . . . . . . . . . . . 2145 . . . . . . . . . . . . . . . . . . . . . . . . . . . .3943 MIAO Deshui . . . . . . . . . . . . . . . 3263 MIAO Haochun . . . . . . . . . . . . . 1581 MIAO JiaYao  ...  . . . . . . . . . . . . . . . 7062 MA Rui . . . . . . . . . . . . . . . . . . . . 1709 MA Rui Jie . . . . . . . . . . . . . . . . . 1917 . . . . . . . . . . . . . . . . . . . . . . . . . . . .8469 MA Shan  ... 
doi:10.23919/ccc52363.2021.9549341 fatcat:z53vt3uelfb6fhymt22le5ea24

Deep learning for photoacoustic imaging: a survey [article]

Changchun Yang, Hengrong Lan, Feng Gao, Fei Gao
2020 arXiv   pre-print
Shan, G. Wang, Y.  ...  Shan, G. Wang, Y.  ... 
arXiv:2008.04221v4 fatcat:rjocswwer5brrg7ibrzke7ps6i

Review of deep learning for photoacoustic imaging

Changchun Yang, Hengrong Lan, Feng Gao, Fei Gao
2021 Photoacoustics  
Jiayao Zhang [54] explored the deep learning algorithms for breast cancer diagnostics, where transfer learning was used to achieve better classification performance.  ...  In other work [98] , Hongming Shan simultaneously reconstructed the initial pressure and sound speed distribution, where SR-net was proposed by fusing the gradients of every iteration with previous pressure  ... 
doi:10.1016/j.pacs.2020.100215 pmid:33425679 pmcid:PMC7779783 fatcat:7nhzn342dvhurkxyvgzpwwuotm

Table of Contents

2021 2021 40th Chinese Control Conference (CCC)   unpublished
GONG Zhen-Yu, GAO Shan-Shan, LIU Yong-Ze, LI Qingkui, PENG Chen 6512 Deterministic Communication Based on TSN and OPC UA Embedded Server . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  ...  XU Jianyou, ZHANG Zhichao, ZHANG Shuo, MIAO JiaYao 6612 Soot Blowing Optimization for Coal-fired Boilers with Ash Accelerated Deposition Model Based on Gamma Process . . . . . . . . . . . . . . . . .  ... 
doi:10.23919/ccc52363.2021.9550117 fatcat:55y7a2gagfhtpc6llmfvl7gqpm
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