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2,176 results on '"Bai, Jie"'

1. Gating Syn-to-Real Knowledge for Pedestrian Crossing Prediction in Safe Driving

Author

Bai, Jie, Fang, Jianwu, Lv, Yisheng, Lv, Chen, Xue, Jianru, and Li, Zhengguo

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

Pedestrian Crossing Prediction (PCP) in driving scenes plays a critical role in ensuring the safe operation of intelligent vehicles. Due to the limited observations of pedestrian crossing behaviors in typical situations, recent studies have begun to leverage synthetic data with flexible variation to boost prediction performance, employing domain adaptation frameworks. However, different domain knowledge has distinct cross-domain distribution gaps, which necessitates suitable domain knowledge adaption ways for PCP tasks. In this work, we propose a Gated Syn-to-Real Knowledge transfer approach for PCP (Gated-S2R-PCP), which has two aims: 1) designing the suitable domain adaptation ways for different kinds of crossing-domain knowledge, and 2) transferring suitable knowledge for specific situations with gated knowledge fusion. Specifically, we design a framework that contains three domain adaption methods including style transfer, distribution approximation, and knowledge distillation for various information, such as visual, semantic, depth, location, etc. A Learnable Gated Unit (LGU) is employed to fuse suitable cross-domain knowledge to boost pedestrian crossing prediction. We construct a new synthetic benchmark S2R-PCP-3181 with 3181 sequences (489,740 frames) which contains the pedestrian locations, RGB frames, semantic images, and depth images. With the synthetic S2R-PCP-3181, we transfer the knowledge to two real challenging datasets of PIE and JAAD, and superior PCP performance is obtained to the state-of-the-art methods., Comment: under review by TITS

Published
2024

8. Development Status and Prospect of Hydrogen Production Technology by Renewable Energy and Its Main Equipment

Author

GE Shuqiang, YANG Zhonggui, BAI Jie, DING Yongchun, WEN Jiahao, and LI Xingyao

Subjects
color classification, hydrogen production by water electrolysis, alkaline electrolyzer, proton exchange membrane, solid oxide, anion exchange membrane, renewable enery, Chemical engineering, TP155-156, Materials of engineering and construction. Mechanics of materials, TA401-492, Technology
Abstract

Purposes Hydrogen energy, as an efficient and clean secondary energy in the 21st century with its high heat value and extremely environmentally friendly combustion products, has become the most promising alternative energy source to replace traditional fossil fuels. The necessity of hydrogen development, promotion, and utilization under the dual-carbon goal of “carbon peaking in 2030 and carbon neutralvty in 2060” as well as the current hydrogen energy development policies and strategic layout in China are analyzed. Methods By investigating the research progresses and achievements of green hydrogen production technologies, the technology of hydrogen production by water splitting and its main devices are summarized, and the development status and trend of hydrogen production by water splitting and the related devices are reviewed. The research status of electrolytic cell and its important components (such as membrane electrode assembly, hydrogen tension bolt assembly and end pressure plate) and the main problems existing in key equipment are analyzed, and the future development trend of alkaline electrolytic cell and proton etchange membrane electrolytic cell are prospected. Conclusion This review provides a reference for the future development of hydrogen production equipment.

Published
2024
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9. Cross-modality Attention Adapter: A Glioma Segmentation Fine-tuning Method for SAM Using Multimodal Brain MR Images

Author

Shi, Xiaoyu, Chai, Shurong, Li, Yinhao, Cheng, Jingliang, Bai, Jie, Zhao, Guohua, and Chen, Yen-Wei

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

According to the 2021 World Health Organization (WHO) Classification scheme for gliomas, glioma segmentation is a very important basis for diagnosis and genotype prediction. In general, 3D multimodal brain MRI is an effective diagnostic tool. In the past decade, there has been an increase in the use of machine learning, particularly deep learning, for medical images processing. Thanks to the development of foundation models, models pre-trained with large-scale datasets have achieved better results on a variety of tasks. However, for medical images with small dataset sizes, deep learning methods struggle to achieve better results on real-world image datasets. In this paper, we propose a cross-modality attention adapter based on multimodal fusion to fine-tune the foundation model to accomplish the task of glioma segmentation in multimodal MRI brain images with better results. The effectiveness of the proposed method is validated via our private glioma data set from the First Affiliated Hospital of Zhengzhou University (FHZU) in Zhengzhou, China. Our proposed method is superior to current state-of-the-art methods with a Dice of 88.38% and Hausdorff distance of 10.64, thereby exhibiting a 4% increase in Dice to segment the glioma region for glioma treatment.

Published
2023

14. Artificial optoelectronic synapse based on CdSe nanobelt photosensitized MoS2 transistor with long retention time for neuromorphic application

Author

Song Xiaohui, Lv Xiaojing, He Mengjie, Mao Fei, Bai Jie, Qin Xuan, Hu Yanjie, Ma Zinan, Liu Zhen, Li Xueping, Shen Chenhai, Jiang Yurong, Zhao Xu, and Xia Congxin

Subjects
cadmium selenide, molybdenum disulfide, heterojunction, artificial synapse, neuromorphic application, Physics, QC1-999
Abstract

Optoelectronic synaptic devices have been regarded as the key component in constructing neuromorphic computing systems. However, the optoelectronic synapses based on conventional 2D transistor are still suffering low photosensitivity and volatile retention behavior, which can affect the recognition accuracy and long-term memory. Here, a novel optoelectronic synaptic device based on surface-state-rich CdSe nanobelt photosensitized 2D MoS2 transistor is demonstrated. Benefiting from the excellent light absorption of CdSe and effective charge trapping at the hetero-interface, the device exhibits not only high photosensitivity but also long retention time (>1,500 s). In addition, typical synaptic functions including the excitatory postsynaptic current, paired-pulse facilitation, the transformation from short-term to long-term plasticity, the transformation from short-term to long-term plasticity, spike-amplitude-dependent plasticity, and learning-forgetting-relearning process are successfully simulated and modulated by light stimulation. Most importantly, an artificial neural network is simulated based on the optical potentiation and electrical habituation characteristics of the synaptic devices, with recognition accuracy rates of 89.2, 93.8, and 91.9 % for file type datasets, small digits, and large digits are achieved. This study demonstrates a simple and efficient way to fabricate highly photosensitive optoelectronic synapse for artificial neural networks by combining the merits of specific materials and device architecture.

Published
2024
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15. Effects of Biological Soil Crusts Development on Soil Erosion Resistance on Loessial Soil

Author

TIAN Jing, WANG Bing, MA Jinlong, BAI Jie, and ZHANG Zhijian

Subjects
surface roughness, soil cohesion, saturated hydraulic conductivity, the mass loss rate, the loess plateau, Environmental sciences, GE1-350, Agriculture
Abstract

[Objective] The extensive development of biological soil crusts driven by the project of “Grain for Green” on the Loess Plateau can significantly inhibit soil erosion, but the characteristics of soil erosion resistance and the response mechanism with the growth and development of biological soil crusts are still unclear. [Methods] Algal crusts, moss crusts, and natural succession crusts were cultivated for 176 days to systematically study the effects of different developmental stages and types of biological soil crusts on loessial soil erosion resistance. [Results] (1)The coverage, thickness, biomass, chlorophyll and roughness of the biological soil crusts increased significantly with growth time, and the moss crusts were higher at the beginning of cultivation and the natural succession crusts were highest at the end of cultivation. (2) With the development of biological soil crusts, the cohesion increased as a power function, which increased by 39.8%~60.3% compared with the initial period; the mass loss rate decreased exponentially, which decreased by 45.6%~57.3% compared with the initial period; and the saturated hydraulic conductivity (Ks) was more complex, but the Ks was lowest at the end of cultivation (0.08~0.12 mm/min). (3) Soil cohesion increased as a power function with the increase of coverage, thickness, chlorophyll, biomass and roughness, and the mass loss rate decreased exponentially with the increase of coverage, thickness, chlorophyll, biomass and roughness. (4) The comprehensive index of soil erosion resistance (Cser) constructed based on soil properties can effectively show the effect of biological soil crusts development on soil erosion resistance. And the Cser can be expressed as a power function of coverage (Cov), thickness (T) and biomass (B) (Cser=0.279 Cov0.194T0.188B0.119, R2=0.73, p

Published
2024
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16. Research on State Detection Method of Complex System Based on Unknown Input

Author

Niu, Wei, Bai, Jie, Zhao, Yangyang, Wang, Sen, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, and Fu, Song, editor

Published
2024
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17. Adaptive Robust Tracking Control for Aerial Work Platform Vehicle with Guaranteed Prescribed Performance

Author

Dai, Jiawen, Zhang, Zheshuo, Zhang, Bangji, Bai, Jie, Yin, Hui, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Jing, Xingjian, editor, Ding, Hu, editor, Ji, Jinchen, editor, and Yurchenko, Daniil, editor

Published
2024
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18. A Lightweight Pedestrian Intrusion Detection Algorithm Based on On-Board Video

Author

Gao, Yang, Qin, Yong, Cao, Zhiwei, Lian, Lirong, Bai, Jie, Ge, Xuanyu, Yu, Hang, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Gong, Ming, editor, Yang, Jianwei, editor, Liu, Zhigang, editor, and An, Min, editor

Published
2024
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19. A Railway Similarity Multiple Object Tracking Framework Based on Vehicle Front Video

Author

Lian, Lirong, Qin, Yong, Cao, Zhiwei, Gao, Yang, Bai, Jie, Ge, Xuanyu, Yu, Hang, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Gong, Ming, editor, Yang, Jianwei, editor, Liu, Zhigang, editor, and An, Min, editor

Published
2024
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20. A Fine-Grained Method for Detecting Defects of Track Fasteners Using RGB-D Image

Author

Ge, Xuanyu, Qin, Yong, Cao, Zhiwei, Gao, Yang, Lian, Lirong, Bai, Jie, Yu, Hang, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Gong, Ming, editor, Yang, Jianwei, editor, Liu, Zhigang, editor, and An, Min, editor

Published
2024
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21. A Foreign Object Detection Method for Railway Overhead Lines Based on Few-Shot Learning

Author

Yu, Hang, Qin, Yong, Cao, Zhiwei, Lian, Lirong, Gao, Yang, Bai, Jie, Ge, Xuanyu, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Gong, Ming, editor, Yang, Jianwei, editor, Liu, Zhigang, editor, and An, Min, editor

Published
2024
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22. A Lightweight Sementic Segmentation Model for Metro Tunnel Scene Based on Vehicle Front Camera

Author

Bai, Jie, Qin, Yong, Cao, Zhiwei, Lian, Lirong, Gao, Yang, Ge, Xuanyu, Yu, Hang, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Gong, Ming, editor, Yang, Jianwei, editor, Liu, Zhigang, editor, and An, Min, editor

Published
2024
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23. Real-Time Monitoring of Aircraft Engines Using a Feedforward Deep Neural Network

Author

Liu, Jiahuan, Bai, Jie, Liu, Shuai, Chinese Society of Aeronautics and Astronautics, Chaari, Fakher, Series Editor, Gherardini, Francesco, Series Editor, Ivanov, Vitalii, Series Editor, Haddar, Mohamed, Series Editor, Cavas-Martínez, Francisco, Editorial Board Member, di Mare, Francesca, Editorial Board Member, Kwon, Young W., Editorial Board Member, Trojanowska, Justyna, Editorial Board Member, and Xu, Jinyang, Editorial Board Member

Published
2024
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24. Depositing boron on Cu(111): Borophene or boride?

Author

Weng, Xiao-Ji, Bai, Jie, Hou, Jingyu, Zhu, Yi, Wang, Li, Li, Penghui, Nie, Anmin, Xu, Bo, Zhou, Xiang-Feng, and Tian, Yongjun

Subjects
Condensed Matter - Materials Science, Condensed Matter - Mesoscale and Nanoscale Physics, Physics - Applied Physics
Abstract

Large-area single-crystal surface structures were successfully prepared on Cu(111) substrate with boron deposition, which is critical for prospective applications. However, the proposed borophene structures do not match the scanning tunneling microscopy (STM) results very well, while the proposed copper boride is at odds with the traditional knowledge that ordered copper-rich borides normally do not exist due to small difference in electronegativity and large difference in atomic size. To clarify the controversy and elucidate the formation mechanism of the unexpected copper boride, we conducted systematic STM, X-ray photoelectron spectroscopy and angle-resolved photoemission spectroscopy investigations, confirming the synthesis of two-dimensional copper boride rather than borophene on Cu(111) after boron deposition under ultrahigh vacuum. First-principles calculations with defective surface models further indicate that boron atoms tend to react with Cu atoms near terrace edges or defects, which in turn shapes the intermediate structures of copper boride and leads to the formation of stable Cu-B monolayer via large-scale surface reconstruction eventually., Comment: 15 pages, 4 figures

Published
2022

25. Deep Virtual-to-Real Distillation for Pedestrian Crossing Prediction

Author

Bai, Jie, Fang, Xin, Fang, Jianwu, Xue, Jianru, and Yuan, Changwei

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence
Abstract

Pedestrian crossing is one of the most typical behavior which conflicts with natural driving behavior of vehicles. Consequently, pedestrian crossing prediction is one of the primary task that influences the vehicle planning for safe driving. However, current methods that rely on the practically collected data in real driving scenes cannot depict and cover all kinds of scene condition in real traffic world. To this end, we formulate a deep virtual to real distillation framework by introducing the synthetic data that can be generated conveniently, and borrow the abundant information of pedestrian movement in synthetic videos for the pedestrian crossing prediction in real data with a simple and lightweight implementation. In order to verify this framework, we construct a benchmark with 4667 virtual videos owning about 745k frames (called Virtual-PedCross-4667), and evaluate the proposed method on two challenging datasets collected in real driving situations, i.e., JAAD and PIE datasets. State-of-the-art performance of this framework is demonstrated by exhaustive experiment analysis. The dataset and code can be downloaded from the website \url{http://www.lotvs.net/code_data/}., Comment: Accepted by ITSC 2022

Published
2022

29. Structure Model and Promotion Path of Action Research Ability of Primary and Secondary School Teachers

Author

QIU Defeng, WANG Siyu, and BAI Jie

Subjects
primary and secondary school teachers, action research, capability structure model, reflective practice, "learning by doing, Theory and practice of education, LB5-3640
Abstract

Action research is a preferred research method among primary and secondary school teachers. However, due to the lack of in-depth understanding of action research, teachers have encountered various challenges in the actual research process. Establishing a structural model for developing action research capabilities can help frontline teachers accurately grasp the essence of action research and truly understand what it is and how to conduct it. Based on research and analysis of relevant literature, combined with teaching practice, a "stepped-multifaceted" ability structure model has been extracted, with core competency elements such as "problem awareness, communication and collaboration skills, research skills, analytical and summarization skills, and reflection and improvement skills". This model visualizes the action research ability of primary and secondary school teachers. Based on this model, the following pathways have been proposed to enhance teachers' action research capabilities and promote their professional development: creating a community that encourages teacher communication and collaboration skills, using the concept of "community" to enhance their participation abilities; using research projects to drive teachers' development of research skills by allowing them to learn through practical experience; encouraging teachers to engage in continuous reflection throughout the entire research process, thereby stimulating their problem awareness and research consciousness; emphasizing the importance of lifelong learning and improving one's abilities through the cyclical process of "learning-action".

Published
2024
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37. TJ4DRadSet: A 4D Radar Dataset for Autonomous Driving

Author

Zheng, Lianqing, Ma, Zhixiong, Zhu, Xichan, Tan, Bin, Li, Sen, Long, Kai, Sun, Weiqi, Chen, Sihan, Zhang, Lu, Wan, Mengyue, Huang, Libo, and Bai, Jie

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence
Abstract

The next-generation high-resolution automotive radar (4D radar) can provide additional elevation measurement and denser point clouds, which has great potential for 3D sensing in autonomous driving. In this paper, we introduce a dataset named TJ4DRadSet with 4D radar points for autonomous driving research. The dataset was collected in various driving scenarios, with a total of 7757 synchronized frames in 44 consecutive sequences, which are well annotated with 3D bounding boxes and track ids. We provide a 4D radar-based 3D object detection baseline for our dataset to demonstrate the effectiveness of deep learning methods for 4D radar point clouds. The dataset can be accessed via the following link: https://github.com/TJRadarLab/TJ4DRadSet., Comment: 2022 IEEE International Intelligent Transportation Systems Conference (ITSC 2022)

Published
2022
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