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检索条件"任意字段=2014 IEEE International Conference on Progress in Informatics and Computing"

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Retrieval of 3D Models Based on Multi-instance

Retrieval of 3D Models Based on Multi-instance

引用

The 2010 ieee international conference on progress in informatics and computing

作者： Lili Wan,Junqing Zhang,Zhenjiang Miao Institute of Information Science Beijing Jiaotong University Beijing,China

A new 3D model retrieval approach is proposed by using multi-instance to understand 3D models,while each object in a 3D model is called *** visually connected components are not geometrically connected,we present a twostage multi-instance generation *** first stage is to compute connected components from a mesh *** second stage is to merge connected components by testing intersections among their axis-aligned bounding *** then shape descriptor is extracted for each instance and the similarity between 3D models is measured by means of instances' shape *** results show that our method has better performance than the traditional 3D model retrieval approach.

关键词： 3D model retrieval shape retrieval MIML connected components

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Free text mining of TCM medical records based on conditional random fields

Free text mining of TCM medical records based on conditional...

引用

2016 ieee international conference on progress in informatics and computing

作者： Qiyu Jiang Hongyi Li Jiafen Liang Guangzhou University of Chinese Medicine

Medical records of Traditional Chinese Medicine(TCM) are usually free text and unstructured data, how to extract medical terms from TCM medical records based on conditional random fields is an interesting problem. TCM medical records obtained from dermatology in Guangdong Provincial Hospital of Chinese Medicine are segmented to single words and labeled with grammatical properties of words by TCM expert, and divided into training sets and testing sets. Clinical terms of training sets are also labeled with clinical terms labeling. In order to evaluate the recognition ability of CRF, three indicators(recognition Precision(P), recognition Recall(R) and F-score(F)) are defined, and three comparisons are given: CRF compared with HMM, ME, and MEMM;Cross test with CRF;and recognition accuracies on different types of clinical terms with CRF. The result shows that, CRF performs a best recognition ability comparing with HMM, ME and MEMM in different groups with different levels of training sets. CRF is credible and stable for different training samples by ten cross test. With the same CRF model, terms of TCM diagnosis can be identified most easily, and terms of symptoms and signs are relatively difficult to identify. So CRF is a suitable model on mining clinical terms in free text of TCM medical records.

关键词： TCM medical records Conditional random fields HMM Text mining

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Hoisting Technique Simulation Based on Physical Engine for Launch Site

Hoisting Technique Simulation Based on Physical Engine for L...

引用

2016 ieee international conference on progress in informatics and computing

作者： Na Chen Pengxiang Yi Xiu Luo Liu Feng Wu Weiqing Li School of Computer Science and Engineering Nanjing University of Sci.& Tech. Beijing Special Engineering Design and Research Institute

Hoisting technique plays an important role of spaceflight test and launch. Simulation of hoisting technique can promote effectivity and safety. Based on finite automata, seven key steps of hoisting technique are analyzed. Double-hook erecting process is designed as a key step, and analyzed the force of the load. The state transition diagram is designed to describe the double-hook erecting. Using ODE as a physics engine, the double-hook erecting is simulated by rigid body kinematic. With physics engine, the force of the object is calculated by rigid body kinematics, and the centroid's displacement is more accurate compared with particle kinematics. Also, simulation using the physics engine provides a certain reference value for the security of staff, the operable range and so on. The hoisting technique simulation system based on physics engine has been applied in launch site.

关键词： hoisting technique process simulation rigid body kinematics ODE

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A Robust Traffic Driver Face Detection Method

A Robust Traffic Driver Face Detection Method

引用

2016 ieee international conference on progress in informatics and computing

作者： Dechao Luo Xiaobo Lu Changhui Hu Xiang Peng Wei Wang School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education

Face detection technology is a hot topic in the past recent years. It has been maturely applied to many practical areas. However, the driver face detection is still an open problem to solve. In this paper, we proposed an improved method to promote the face detection rate and apply it to the images from the monitoring videos. The first step is to detect the car from the images according to an off-line learning method. Then the method based on additional off-line learning method is the front level for skin color feature in order to correctly detect the driver face. The proposed systems are implemented on the various complicated road environment. The results show that the proposed method improves the efficiency of the driver face detection and is of strong robustness on having glasses, driver head rotation, and lighting change.

关键词： car detection driver face detection skin color feature Haar-like feature Adaboost

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A UAV Edge computing Task Offloading Method Based on Reinforcement Learning and the Underwater Lobster Optimization Algorithm

A UAV Edge Computing Task Offloading Method Based on Reinfor...

引用

Symposium of Image, Signal Processing, and Artificial Vision (STSIVA)

作者： Keqin Jiang Mingyan Jiang Dongfeng Yuan Ze Zhao School of Information Science and Engineering Shandong University Qingdao China Qilu Institute of Technology Jinan China

ISBN: (数字)9798350363203

ISBN: (纸本)9798350363210

With the rapid development of UAV edge computing, the randomness of task generation and the unpredictability of UAV mobility have made related problems increasingly complex. This not only poses a highly intricate integer optimization problem but also requires swift and effective decision-making based on real-time monitoring. Traditional offline algorithms face numerous challenges in addressing such issues and often struggle to meet the demands of dynamic environments. In response, this paper proposes an innovative heuristic algorithm-the V nderwater Lobster Optimization Algorithm-combined with reinforcement learning techniques to dynamically learn the optimal data transmission path. Through this approach, we can flexibly adjust the optimization algorithm's update strategy, effectively achieving dynamic management goals and improving the system's overall performance and response speed. The proposed algorithm successfully addresses the task offloading problem in UAV edge computing. Experimental results show that the algorithm significantly reduces system response time and improves task completion rates, fully demonstrating its potential and advantages in the field of AV edge computing.

关键词： Heuristic algorithms Reinforcement learning Autonomous aerial vehicles Dynamic scheduling Real-time systems Data communication Time factors Optimization Edge computing Drones

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Using Adaboost and SIFT for Capturing Chinese Text Content of Natural Scene Image in Mobile Communication Network

Using Adaboost and SIFT for Capturing Chinese Text Content o...

引用

The 2010 ieee international conference on progress in informatics and computing

作者： ShaoQing Li,Chuang Zhang,ZhiQing Lin Pattern Recognition & Intelligent System Lab Beijing University of Posts and Telecommunications Beijing 100876,China

The Chinese text in natural scene images which are transmitted in mobile communication network usually contains various and important ***,capturing Chinese text in these images can analyze the content of these images,and improve the commercial value and security of our *** paper proposes an efficient and effective method to capture the Chinese text in images which were taken by mobile phone in natural *** detection and the location of the target text are achieved by AdaBoost,which can eliminate background noise;the SIFT feature,which is proper to the characteristics of Chinese text in image,is applied to capture the content of the located *** method has a good practical application *** the lack of experimental samples,further research is needed to improve.

关键词： Chinese Text Adaboost SIFT Natural Scene Mobile recognition detection

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TOPSIS multiple attribute decision making method based on three parameters interval number

TOPSIS multiple attribute decision making method based on th...

引用

2016 ieee international conference on progress in informatics and computing

作者： Yuan Rong Yi Liu School of Mathematics and Information Science Neijiang Normal University Data Recovery Key Lab of Sichuan Province Neijiang Normal Univeristy

in order to study the three parameters interval number multiple attribute decision making problems, the three parameters interval number of Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS) multiple attribute decision making method are introduced, the relationship between three parameters interval number operation are set up,the Euclidean distance of the three parameters interval number and positive and negative ideal solution is also defined, by calculating Euclidean distance of each alternative solutions to the ideal point and approximation degrees, according to the size of the approximation degree of implementation in order of alternatives. Finally through the concrete case illustrates the validity and practicability of the method, and to solve the interval number multiple attribute decision making provides a new path.

关键词： three parameters interval number Multiple attribute decision making TOPSIS Approximation degree

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GMM Based Classification of Speech under Stress Using Physical Features

GMM Based Classification of Speech under Stress Using Physic...

引用

2016 ieee international conference on progress in informatics and computing

作者： Xiao Yao Ning Xu Mingsheng Gao Aiming Jiang Xiaofeng Liu The College of Io T Engineering Hohai University

Physical stress from workload for speaker exerts limitations on his speech production in physiological system causing speech variability, and thereby reduces speech system performance. The speech under stress presents a marked difference from the speech under neural condition. The distribution for the stress samples in the feature space shows the discontinuity because of the existence of different stress levels and different physiological characteristics for each speaker under the stress condition. In this paper, we use a Gaussian Mixture Models（GMM） framework with the physical features derived from the speech production model for neutral/stress speech classification. Cluster analysis is performed within stress class, and several cluster areas can be found for the classification, which is following Gaussian distribution. Experimental results show that GMM outperforms other classifiers for differentiating neutral speech from stress.

关键词： stress classification physiological system gaussian mixture model physical feature

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Work in progress: Influence of cognitive concept connection, personal motivations, and personal characteristics when assessing creativity 124

Work in progress: Influence of cognitive concept connection,...

引用

124th ASEE Annual conference and Exposition

作者： Wu, Ting-Ting Huang, Yueh-Min Ray National Yunlin University of Science and Technology Taiwan National Cheng-Kung University Taiwan

Industry now requires interdisciplinary and creative thinking skills because of a paradigm shift in target markets. Therefore, modern engineering education should focus on developing students' innovative thinking for solving engineering problems and design courses to foster students' creativity, critical thinking, and ability to transfer their skills. This study employed the widely used Moodle learning platform for courses on computer science and engineering. Appropriate guidance from the platform regarding the different objectives of five project stages enabled group members to communicate, exchange, and interact, and the students gradually developed their thinking from divergent to convergent. Through deep analysis of the students' learning portfolios, the effects of cognitive concepts, personal motivations, and personal characteristics on creativity were investigated. Moreover, this study further explored three issues regarding the differences between highly and lowly creative students so that teachers could employ appropriate teaching resources or assistance. The findings of this study can help teachers provide timely guidance and responses to students. Fostering students' creative thinking and unleashing their imagination thus develops their capacity for innovation, which is now essential in engineering education. © American Society for Engineering Education, 2017.

关键词： Students

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Incremental Learning for Object Detection Based on Self-Supervised Learning

Incremental Learning for Object Detection Based on Self-Supe...

引用

Symposium of Image, Signal Processing, and Artificial Vision (STSIVA)

作者： Haihong Sheng Jiapeng Zhang Lu Wan Zheng Huang Pengzuo Wu Qiang Wang Information Technology Department Zhejiang Huayun Information Technology Co. Ltd. Hangzhou China College of Computer Science and Technology Zhejiang University Hangzhou China

ISBN: (数字)9798350363203

ISBN: (纸本)9798350363210

Incremental learning, as an approach well-suited for handling applications characterized by evolving data streams, aligns effectively with the objectives of object detection. However, existing methods exhibit suboptimal performance in addressing issues related to catastrophic forgetting and few-shot learning of new classes. Through the enhancement of existing models, we propose a novel method that integrates self-supervised learning. By employing a feature-prediction collaborative mechanism and gradient stopping techniques, the method significantly enhances the model's generalization capability for new category features while also mitigating the forgetting of old category knowledge during the incremental learning process to some extent. Experimental results demonstrate that the proposed method maintains detection performance for old categories throughout multiple incremental learning phases while simultaneously improving the learning capacity for new categories.

关键词： Incremental learning Collaboration Self-supervised learning Object detection informatics Few shot learning Streams

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