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检索条件"机构=CETC Key Laboratory of Data Link Technology"

共 107 条记录，以下是41-50 订阅

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Object Recognition Through UAV Observations Based on Yolo and Generative Adversarial Network 6th

Object Recognition Through UAV Observations Based on Yolo an...

引用

6th EAI International Conference on IoT as a Service, IoTaaS 2020

作者： Li, Bo Gan, Zhigang Neretin, Evgeny Sergeevich Yang, Zhipeng School of Electronics and Information Northwestern Polytechnical University Xi’an China CETC Key Laboratory of Data Link Technology Xi’an China Moscow Aviation Institute Moscow Russia

ISBN: (纸本)9783030675134

Aiming at the object recognition through UAV, an intelligent object recognition model based on YOLO and Generative adversarial network is proposed in this paper. Firstly, the solution is given, and an object recognition model that can realize intelligent recognition is established. Then, in order to improve the resolution of the identified images, an image resolution enhancement model based on generative adversarial networks is built. After that, the structure and parameters of the recognition model and image resolution enhancement model are adjusted through the simulation experiments to improve the accuracy and robustness of the object recognition. Finally, the object recognition model based on YOLO and generative adversarial network in this paper is verified through UAV. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Object recognition

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Redundancy Reduction of Musculoskeletal Model for Robots with Group Sparse Neural Network 6

Redundancy Reduction of Musculoskeletal Model for Robots wit...

引用

6th International Conference on Control and Robotics Engineering, ICCRE 2021

作者： Zhong, Shanlin Zhang, Jinhan Nie, Xiangli Institute of Automation Chinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Science Beijing China CETC Key Laboratory of Data Link Technology Xi'an China

ISBN: (纸本)9780738126128

Creating robots with similar behavior and appearance to humans has been a long-term dream for roboticists. However, the highly redundant characteristic of the muscle system brings tremendous difficulty for the control and manufacture of the musculoskeletal robot. In this paper, we propose a heuristic pruning-based recurrent neural network method with group sparse regularization to reduce redundancy of muscles in musculoskeletal model, which can maintain the motion accuracy of musculoskeletal robots without activating the redundant muscles. Experiments on an upper extremity musculoskeletal model validate the effectiveness of the proposed method. © 2021 IEEE.

关键词： Recurrent neural networks

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BEBLID-SLAM: An Efficient Feature-Based Monocular SLAM System

BEBLID-SLAM: An Efficient Feature-Based Monocular SLAM Syste...

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Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Feng Yang Baibing Jie Hongxuan Song Haotian Li Key Laboratory of Information Fusion Technology Ministry of Education Northwestern Polytechnical University Xi’an China CETC Key Laboratory of Data Link Technology Northwestern Polytechnical University Xi’an China

ISBN: (纸本)9781665465373

The feature matching quality plays an important role in the robustness and location accuracy of feature-based Simultaneous Localization and Mapping (SLAM) system, in which descriptor is significant of tracking and re-localization. In this paper, we propose an efficient feature-based Monocular SLAM system, BEBLID-SLAM, which use BEBLID descriptor for feature matching in ORB-SLAM pipeline. In the proposed system, adopting histogram equalization to preprocess input images and offline training Bag-of-Words for BEBLID is respectively adopted to preprocess input images and realize re-localization and loop closure. Moreover, we valided that our algorithm has outstanding performance in robustness and accuracy than the popular algorithms in the public dataset EuRoC

关键词： Training Histograms Simultaneous localization and mapping Automation data preprocessing Pipelines Robustness

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Design of real-time vehicle detection based on YOLOv4 10

Design of real-time vehicle detection based on YOLOv4

引用

10th International Conference on Control, Automation and Information Sciences, ICCAIS 2021

作者： Yang, Feng Zhang, Xingle Zhang, Shuxing Li, Chao Hu, Haiwei Northwestern Polytechnical University CETC Key Laboratory of Data Link Technology Xi'an710072 China Institute No.206 of China Arms Industry Group Corporation Xi'an710100 China

ISBN: (纸本)9781665440295

Intelligent Traffic System (ITS), whose key point is vehicle detection, can significantly reduce the incidence of traffic accidents through scientific traffic control. Traditional vehicle detection technology has unsatisfactory detection speed and accuracy. In order to obtain and process object feature information more efficiently, we use the convolutional neural network (CNN) with better performance. In addition, compared with traditional computers with large volume and high computing cost, the embedded platform is more suitable for deployment model in practical application. Based on the convolutional neural network YOLOv4, we deploy it on the embedded platform, and optimizes the Class-imbalance of BDD100K dataset used in the model and the lack of real-time performance of the model. After optimization, for the BDD100K dataset, the detection accuracy of the model is improved by 2.81%, and the detection speed is improved to 28.45 FPS, which can meet the requirements of real-time vehicle detection. © 2021 IEEE.

关键词： Convolutional neural networks

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A Phase Noise Immune Equalization Algorithm For Millimeter Wave SC-FDE System

A Phase Noise Immune Equalization Algorithm For Millimeter W...

引用

International Conference on Computer Science and Network technology (ICCSNT)

作者： Yu Wang Yuanyuan Xu National Key Laboratory of Multi-Domain Data Collaborative Processing and Control China Electronics Technology Group Corporation (CETC) 20th Institute Xi’an China

ISBN: (数字)9798350350791

ISBN: (纸本)9798350350807

To solve the problem that phase noise affection of high-order modulation in millimeter wave broadband system, this paper analyzes and modifies the theoretical model of phase noise provided in the 802.11ad and 802.15.3c standards, and generates the actual noise values based on the modified model for simulation analysis. The frame structure given in standards is optimized for SC-FDE system to estimate noise and channel state by adding data block 0. An improved MMSE equalization algorithm is proposed in this paper to track the channel and phase noise changes in real time and obvious phase noise immunity characteristic is obtained compared with traditional algorithm.

关键词： Phase noise IEEE 802.15 Standard Computer science Analytical models Phase modulation Millimeter wave technology Channel estimation Real-time systems Broadband communication Standards

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A High-Speed Stable Polarization Encoder for Quantum key Distribution 16

A High-Speed Stable Polarization Encoder for Quantum Key Dis...

引用

16th Pacific Rim Conference on Lasers and Electro-Optics, CLEO-PR 2024

作者： Li, Ju Wang, Zexu Wang, Changlei Yin, Feifei Xu, Kun Xu, Huaxing Dai, Yitang Beijing University of Posts and Telecommunications State Key Laboratory of Information Photonics and Optical Communications Beijing100876 China National Engineering Research Center for Public Safety Risk Perception and Control by Big Data China Academy of Electronics and Information Technology Beijing100041 China Cetc Academy of Electronics and Information Technology Group Co. Ltd. Beijing100041 China

We report a high-speed polarization encoder which can be applied for quantum key distribution, resulting in an average bit error rate (BER) below 0.1% at a repetition frequency of 10 GHz under interference-free measur... 详细信息

ISBN: (纸本)9798350372076

关键词： Quantum cryptography

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Path Planning technology of Unmanned Vehicle Based on Improved Deep Reinforcement Learning 40

Path Planning Technology of Unmanned Vehicle Based on Improv...

引用

40th Chinese Control Conference, CCC 2021

作者： Zhang, Kai Wang, Luhe Hu, Jinwen Xu, Zhao Guo, Chubing Cetc Key Laboratory of Data Link Technology Xi'an710068 China Northwestern Polytechnical University School of Automation Xi'an710129 China Northwestern Polytechnical University School of Electronics and Information Xi'an710129 China

ISBN: (纸本)9789881563804

As the basic problem of unmanned vehicle navigation control, path planning has been widely studied. Reinforcement learning (RL) has been found an effective way of path optimization for the highly nonlinear and unmodeled dynamics. However, the RL based methods suffer from the "dimension disaster"under the high-dimension state spaces. In this paper, the path planning of an unmanned vehicle with collision avoidance is considered, and an improved Deep Q-Network (DQN) algorithm is proposed to reduce the computation load in the high-dimension state space. First, the states, actions and rewards are determined based on the task requirement, and a smoothing function is defined as an additional penalty term to modify the basic reward function. Then, the two-dimension grid of the state space is mapped to a gray image, which is applied as the input of a neural network, i.e., the Q-Network. Finally, simulation results show that the modified DQN algorithm is more stable and the fluctuation frequency is significantly reduced. © 2021 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Motion planning

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Information value measurement distribution model based on improved information entropy 4

Information value measurement distribution model based on im...

引用

4th IEEE International Conference on Electronic Information and Communication technology, ICEICT 2021

作者： Chen, Liang Chen, Chilian Zhao, Lulu Key Laboratory of Technology on Data link China Electronics Technology Group Corporation 20th Institute Xi’an China

ISBN: (纸本)9781665432030

in order to meet the needs of modern war for high-quality situation information, this paper first proposes a battlefield situation information value measurement model based on improved information entropy from the perspective of battlefield situation information. According to the situation information index system, the degree of information demand satisfaction, and the principle of minimum error, the information entropy is improved to realize the battlefield situation information value measurement. Then, referring to link16’s distributed route selection algorithm based on R2 reporting responsibility, a message distribution algorithm based on information value is designed to give priority to the transmission of high-value information flow in the network. Finally, the effectiveness of the algorithm is verified by the simulation of typical combat scenarios of close air support, especially in the case of strong confrontation environment. © 2021 IEEE

关键词： Weight measurement Atmospheric modeling Conferences Measurement uncertainty Interference Time measurement Information and communication technology

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NLP based on prompt-based learning and prompting methods: a survey

NLP based on prompt-based learning and prompting methods: a ...

引用

5th International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM 2023)

作者： L. Zhao Q. Li A. Tariq J. Yang Key Laboratory of Technology on Data link China Electronics Technology Group Corporation (CETC) 20th Institute Xi'an 710072 People's Republic of China School of computer science Northwestern Polytechnical University Xi'an 710072 People's Republic of China

In this survey paper, we attempted to summarize the recent work of a paradigm shift in the natural processing language field that we call "Prompt-based learning". In recent years, the rapid development and stability of pre-trained language models have driven the advancement of this novel approach. Prompt-based learning leverages language models for clue-driven learning and has made significant strides in the field of natural language processing. To make predictions, the process begins with the design of text prompts based on the nature of the task and input-output format. Subsequently, user input data is combined with these text prompts to create a new text sequence, which is then fed into a pre-trained language model. Following this, information required for the task is extracted or interpreted from the generated text, and ultimately, the interpreted results are presented to the user or used for further processing, depending on the task requirements. However, there is currently no standardized framework for prompt-based learning. Existing code libraries for prompt-based learning are typically unregulated and provide limited functionality tailored to specific scenarios. Therefore, this paper aims to elucidate the theoretical foundations, various mathematical approaches, and existing research methodologies, as well as key aspects such as model selection, prompt optimization processes, and practical applications of prompt-based learning.

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Tactical data Chain link Effectiveness Assessment Based on Cloud Theory

Tactical Data Chain Link Effectiveness Assessment Based on C...

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IEEE International Conference on Electronic Information and Communication technology (ICEICT)

作者： Liang Chen FuQiang Li Lulu Zhao Qian Zhang Key Laboratory of Technology on Data link China Electronics Technology Group Corporation 20th Institute Xi'an China Xi'an China

To address the complexity of tactical data chain system effectiveness assessment, a tactical data chain system effectiveness assessment index system is established by drawing on the principles of cloud theory, and a tactical data chain system effectiveness assessment method based on cloud theory is proposed. Based on the description of the hierarchical analysis method and the evaluation steps of cloud theory, the evaluation of the effectiveness of the tactical data chain system is realized by calculating the cloud model of each indicator and the weight of each indicator parameter in combination with a specific example. The example proves that this method can effectively integrate the uncertainty and ambiguity of quantitative and qualitative indicators, is highly operable, and can provide a scientific and objective method for the comprehensive effectiveness assessment of tactical data chain systems based on network information systems.

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