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Image Hashing Based on SIFT Features 21

Image Hashing Based on SIFT Features

引用

4th International Conference on computer Science and Software Engineering, CSSE 2021

作者： Li, Pingyuan Yuan, Xiaoguang Jiang, Suiping Beijing Institute of Computer Technology and Applications China

ISBN: (纸本)9781450390675

Image hashing maps high-dimensional image to low-dimensional binary code which can be used for fast image retrieval. A new image hashing method is proposed in this paper. Firstly, the SIFT features of an image are extracted. Secondly, the SIFT feature's 128 dimensional components are divided into 16 groups and the differential SIFT feature of each group is calculated in a sequential and cyclic way. Thirdly, the weight of each SIFT feature is calculated and is applied to the corresponding differential SIFT feature. Finally, the weighted differential SIFT features are summed to get the image's SIFT feature, and binarization is carried out on each group of the image's SIFT feature in a sequential and cyclic way to obtain the hash code of the image. The proposed method has the advantage that it can quickly generate hash codes for large-scale data sets and is robust to rotation and noise. The experimental results on caltech-256 showed that the proposed method can improve the effect of image retrieval. © 2021 ACM.

关键词： Image retrieval

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Two-Stage Origami-Based Vibration Isolators with High-Static-Low-Dynamic-Stiffness Characteristics

Two-Stage Origami-Based Vibration Isolators with High-Static...

引用

ASME/IFToMM International Conference on Reconfigurable Mechanisms and Robots, ReMAR

作者： Shiwei Liu Shengnan Lyu Qiuyue Zheng Xilun Ding Mechanical Engineering and Automation Beihang University Beijing China Beijing Institute of Computer Technology and Applications Beijing China

ISBN: (数字)9798350395969

ISBN: (纸本)9798350395976

This paper focuses on the structure, dynamics, and isolation performance of the proposed two-stage high-static-low-dynamic-stiffness (HSLDS) vibration isolator consisting of two Tachi-Miura origami units in series. Torsion springs are placed at creases to introduce elastic effect into the origami-based vibration isolator. Employing the nonlinear stiffness properties of Tachi-Miura origami, the HSLDS characteristics of the isolator unit are achieved by adjusting the stiffness coefficient of the spring at the creases. Moreover, an equivalent dynamic model of the coupled origami-based isolator is established; the analytical steady-state behavior is obtained. The force trans-missibility results and comparative analysis demonstrate the effectiveness of the presented two-stage origami-based isolator in low-frequency vibration isolation.

关键词： Vibrations Isolators Analytical models Force Dynamics Bandwidth Harmonic analysis

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Requirement Consistency and Integrity Verification Method based on Natural Language Processing

Requirement Consistency and Integrity Verification Method ba...

引用

2020 International Conference on Industrial applications of Big Data and Artificial Intelligence, BDAI 2020

作者： Wu, Chao Huang, Zhong Hua Yang, Yu Ting Liu, Yue Beijing Institute of Computer Technology and Applications BeiJing100854 China

In the iterative process of the update of the information service system, the continuous improvement of the system is restricted due to problems such as non-standard, incomplete, and strong ambiguity in the description of requirements. It makes it difficult to verify the consistency and integrity of requirements. In this paper, we focus on the huge requirements of complex information service system, and propose research on requirement itemized extraction and structured description technology based on natural language processing and requirement item keyword extraction and standardized expression technology. The library management system is used as the verification object to verify the effectiveness of the method proposed in this paper. © Published under licence by IOP Publishing Ltd.

关键词： Extraction

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Research on Intelligent Cloud Test Platform

Research on Intelligent Cloud Test Platform

引用

2020 International Conference on Industrial applications of Big Data and Artificial Intelligence, BDAI 2020

作者： Zhonghua, Huang Yuting, Yang Jing, Gao Kunlong, Wang Beijing Institute of Computer Technology and Applications Beijing100854 China

With the increasing complexity of software information systems, software quality assurance faces enormous challenges. The software information system is more and more complex, and the quality requirements are getting higher and higher. The traditional automated test methods and tools can not adapt to the changing test requirements. The research on the independent controllable intelligent test platform based on cloud computing and big data will be carried out. The combination of platform and software testing not only reduces test costs, but also improves test efficiency and effectiveness. This paper analyzes the status quo and gaps of the intelligent cloud test platform at home and abroad, and presents the research content and technical solutions of an autonomous and controllable intelligent cloud test platform. First, we make research on the rapid construction technology of large-scale test environment for heterogeneous independent platforms,that is, mirror virtualization and rapid combined deployment technology of software testing tool environment;secondly,we study complex business scenario model generation technologies, including domain analysis and modeling of information systems, formal definition of model-based complex business scenarios and rapid construction technology;finally, we study the automatic generation technology of test cases for complex business scenarios, aiming to make full use of complex business scenario models and full-link historical test data. © Published under licence by IOP Publishing Ltd.

关键词： Information systems

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Historical Information-Based Intent Detection for Multiturn Dialogue 22

Historical Information-Based Intent Detection for Multiturn ...

引用

8th International Conference on Computing and Artificial Intelligence, ICCAI 2022

作者： Sun, Xin Zheng, Hongchao Tang, Zheng Beijing Eng. Res. Ctr. of High Vol. Language Information Processing and Cloud Computing Applications School of Computer Science and Technology Beijing Institute of Technology Beijing100081 China School of Computer Science and Technology Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9781450396110

Intent detection aims to determine the intent of users, an important task in natural language processing and dialogue systems. As one of the key modules of task-based dialogue systems, intent detection directly influences the meaning analysis of spoken language and the performance of dialogue systems. However, existing intent detection algorithms mainly focus on single-turn conversation, ignoring the valuable historical conversation message. To alleviate the problem, we propose a multiturn dialogue intent detection model based on historical information. Specifically, the semantic information of user statements and system statements is extracted by a role-distinguished self-attention network. Then, semantic relevance based on context information adjustment is used to combine the system statement and user statement. Finally, long short-term memory (LSTM) is used to capture the historical message. Experimental results prove that the proposed method improves the effect of intent detection and performs better than seven mainstream baselines. © 2022 ACM.

关键词： Long short-term memory

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Augmenting Context Representation with Triggers Knowledge for Relation Extraction 12th

Augmenting Context Representation with Triggers Knowledge fo...

引用

12th IFIP TC 12 International Conference on Intelligent Information Processing, IIP 2022

作者： Li, En Shi, Shumin Yang, Zhikun Huang, He Yan School of Computer Science and Technology Beijing Institute of Technology Beijing China Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications Beijing China

ISBN: (纸本)9783031039478

Relation Extraction (RE) requires the model to classify the correct relation from a set of relation candidates given the corresponding sentence and two entities. Recent work mainly studies how to utilize more data or incorporate extra context information especially with Pre-trained Language Models (PLMs). However, these models still face with the challenges of avoiding being affected by irrelevant or misleading words. In this paper, we propose a novel model to help alleviate such deficiency. Specifically, our model automatically mines the triggers of the sentence iteratively with the sentence itself from the previous iteration, and augment the semantics of the context representation from BERT with both entity pair and triggers skillfully. We conduct extensive experiments to evaluate the proposed model and effectively obtain empirical improvement in TACRED. © 2022, IFIP International Federation for Information Processing.

关键词： Semantics

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Conflict-Driven Intention Negotiation Based on Reinforcement Learning in Intent Defined Optical Networks 27

Conflict-Driven Intention Negotiation Based on Reinforcement...

引用

27th OptoElectronics and Communications Conference/International Conference on Photonics in Switching and Computing, OECC/PSC 2022

作者： Teng, Yun Shen, Yuefeng Yang, Hui Bao, Bowen Yao, Qiuyan Wang, Lvda Beijing University of Posts and Telecommunications State Key Laboratory of Information Photonics and Optical Communications China Beijing Institute of Computer Technology and Applications Beijing China

In intent defined optical networks, an intent defined conflict negotiation scheme based on reinforcement learning is proposed. The simulation results show that the scheme can effectively improve the utilization of net... 详细信息

ISBN: (数字)9784885523366

ISBN: (纸本)9784885523366

关键词： Reinforcement learning

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Joint Learning of Multi-Level Tasks for THz Image Perception in Robots

Joint Learning of Multi-Level Tasks for THz Image Perception...

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International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： Haoming Liu Xinhua Li Ye Zou Yuting Yang Zhi Fang Youchen Wang Data Technology and Applications Department Beijing Institute of Computer Technology and Application Beijing China Department of Automation Tsinghua University Beijing China

ISBN: (数字)9798350385724

ISBN: (纸本)9798350385731

THz imaging has gained widespread attention due to its high penetration ability and safety. However, THz systems deployed on robotic platforms are limited by their low resolution and high noise levels, which restrict their appeal in low-level human visual perception and application in high-level visual downstream tasks. In this research, we proposed an algorithmic framework featuring a $\mathbf{U}$-shaped feature extraction network and an image reconstruction module. Based on this, we introduced a multi-task loss function for joint learning. Through lightweight design, the framework is made deployable on low-power robotic platforms. We have also proposed a THz dataset suitable for multi-task applications. This framework has demonstrated exceptional performance in multi-level visual applications.

关键词： Visualization Mechatronics Image resolution Imaging Multitasking Safety Robots Image reconstruction Visual perception Noise level

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Unsupervised Question Answering via Answer Diversifying 29

Unsupervised Question Answering via Answer Diversifying

引用

29th International Conference on Computational Linguistics, COLING 2022

作者： Nie, Yuxiang Huang, Heyan Chi, Zewen Mao, Xian-Ling School of Computer Science and Technology Beijing Institute of Technology Beijing China Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications Beijing China Beijing Institute of Technology Southeast Academy of Information Technology Fujian China

Unsupervised question answering is an attractive task due to its independence on labeled data. Previous works usually make use of heuristic rules as well as pre-trained models to construct data and train QA models. However, most of these works regard named entity (NE) as the only answer type, which ignores the high diversity of answers in the real world. To tackle this problem, we propose a novel unsupervised method by diversifying answers, named DiverseQA. Specifically, the proposed method is composed of three modules: data construction, data augmentation and denoising filter. Firstly, the data construction module extends the extracted named entity into a longer sentence constituent as the new answer span to construct a QA dataset with diverse answers. Secondly, the data augmentation module adopts an answer-type dependent data augmentation process via adversarial training in the embedding level. Thirdly, the denoising filter module is designed to alleviate the noise in the constructed data. Extensive experiments show that the proposed method outperforms previous unsupervised models on five benchmark datasets, including SQuADv1.1, NewsQA, TriviaQA, BioASQ, and DuoRC. Besides, the proposed method shows strong performance in the few-shot learning setting. © 2022 Proceedings - International Conference on Computational Linguistics, COLING. All rights reserved.

关键词： Natural language processing systems

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Application of 5G+AI technology in agricultural administrative law enforcement

Application of 5G+AI technology in agricultural administrati...

引用

Control, Electronics and computer technology (ICCECT), IEEE International Conference on

作者： Xiaorou Ping Qin Zou Liting Sun General Organization Department Beijing Institute of Computer Technology and Applications Beijing China

This paper analyzes the current situation, existing problems and demands of China's agricultural administrative law enforcement, studies the application scenarios of 5G such as high speed, low delay and massive connection, describes the performance indicators and technical characteristics of 5G, and proposes an agricultural law enforcement application platform based on 5G+AI technology in combination with the development status and technical characteristics of AI. With the help of key technologies such as 5G high-speed network and AI video detection and identification, the platform has the capabilities of intelligent perception, real-time monitoring, analysis, research and judgment, and early warning of law enforcement risks, comprehensively improving the efficiency of agricultural law enforcement.

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