Proceedings of the 2019 International Conference on Robotics Systems and Vehicle Technology - RSVT '19最新文献_第3页

Text Representation Method Combining Multi- level Semantic Features 结合多层语义特征的文本表示方法

Proceedings of the 2019 International Conference on Robotics Systems and Vehicle Technology - RSVT '19 Pub Date : 2019-10-16 DOI: 10.1145/3366715.3366739

Yue Chai, Tongzhou Zhao, Yiqi Jiang, Peidong Gao, Xuan-zhong Li

引用次数: 0

Parallel Sentimental Analysis Based on Nectar Research Cloud and AURIN 基于花蜜研究云和AURIN的平行情感分析

Proceedings of the 2019 International Conference on Robotics Systems and Vehicle Technology - RSVT '19 Pub Date : 2019-10-16 DOI: 10.1145/3366715.3366730

Zhenwei Wang, Mingdong Zhu, Haitao Wang, Wenqian Yang

引用次数: 0

Chinese Word Segmentation Based on Maximum Entropy 基于最大熵的中文分词方法

Proceedings of the 2019 International Conference on Robotics Systems and Vehicle Technology - RSVT '19 Pub Date : 2019-10-16 DOI: 10.1145/3366715.3366741

Xiaolin Li, Zerong Hu, Tao Lu

{"title":"Chinese Word Segmentation Based on Maximum Entropy","authors":"Xiaolin Li, Zerong Hu, Tao Lu","doi":"10.1145/3366715.3366741","DOIUrl":"https://doi.org/10.1145/3366715.3366741","url":null,"abstract":"Chinese word segmentation has received extensive attention in recent years. The word segmentation method based on character-based tagging improves the performance of word segmentation greatly. This method transforms the word segmentation problem into a sequence labeling problem, which has become the main word segmentation method. In order to further study the word segmentation performance of this method, we use the maximum entropy sequence labeling model in this paper. We used two different word position sets and three feature templates to compare the experimental results. We have done further research on the unknown words and segmentation ambiguity in the word segmentation results. First we combined N-Gram with cohesion and degree of freedom to solve the problem of unknown words. Then the maximum entropy model is used to train the new participle to eliminate the ambiguity. The closed test was conducted on the Bakeoff 2005 corpus of the international Chinese word segmentation evaluation. Experiments show that the six-tag position combined with the corresponding feature templates can achieve better word segmentation performance. After adding unknown words and disambiguation processing, the word segmentation performance of some data sets can be further improved to optimal results of Bakeoff 2005.","PeriodicalId":425980,"journal":{"name":"Proceedings of the 2019 International Conference on Robotics Systems and Vehicle Technology - RSVT '19","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128689318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Research of Image Mosaic Techniques Based on Optimized SIFT Algorithm 基于优化SIFT算法的图像拼接技术研究

Proceedings of the 2019 International Conference on Robotics Systems and Vehicle Technology - RSVT '19 Pub Date : 2019-10-16 DOI: 10.1145/3366715.3366737

Ziyun Huang, Haihui Wang, Yanan Li

{"title":"The Research of Image Mosaic Techniques Based on Optimized SIFT Algorithm","authors":"Ziyun Huang, Haihui Wang, Yanan Li","doi":"10.1145/3366715.3366737","DOIUrl":"https://doi.org/10.1145/3366715.3366737","url":null,"abstract":"Image mosaic refers to the process of stitching multiple images those have overlapping areas of small perspective and low resolution into a panoramic image with high resolution and wide perspective through the corresponding image registration and fusion algorithm. In the mosaic of panoramic images, the traditional SIFT algorithm has large amount of calculation that leads to mismatching and unsatisfactory splicing effect in the process of generating feature vectors and performing feature matching. To this end, this paper proposes an optimized SIFT algorithm. The optimization algorithm, at the first time, introduces the Laplacian operator in order to sharpen the edges of the image. Then, based on the SIFT algorithm, matching the feature points by bidirectional matching algorithm. Finally, in the part of image fusion, an algorithm of luminance weight fusion in HSI color space is proposed. Experiments show that compared with the traditional SIFT algorithm, the proposed optimization algorithm can effectively reduce the error matching and improve the matching accuracy of feature points. In the image fusion part, the phenomenon of ghost image and the sudden change of luminance during image mosaic is effectively eliminated, besides the fusion effect is optimized, and ends with a good image mosaic result.","PeriodicalId":425980,"journal":{"name":"Proceedings of the 2019 International Conference on Robotics Systems and Vehicle Technology - RSVT '19","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124742015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Res-RNN Network and Its Application in Case Text Recognition Res-RNN网络及其在大小写文本识别中的应用

Proceedings of the 2019 International Conference on Robotics Systems and Vehicle Technology - RSVT '19 Pub Date : 2019-10-16 DOI: 10.1145/3366715.3366729

Jun Liu, Zhuang Du, Yang Liu

引用次数: 0

Research on Gaussian-wavelet-type Activation Function of Neural Network Hidden Layer Based on Monte Carlo Method 基于蒙特卡罗方法的神经网络隐层高斯-小波型激活函数研究

Proceedings of the 2019 International Conference on Robotics Systems and Vehicle Technology - RSVT '19 Pub Date : 2019-10-16 DOI: 10.1145/3366715.3366732

Jiawei Ji, Ziqiang Zhang, D. Kun, Ruixiao Zhang, Zhixin Ma

引用次数: 2

Mobile Robot Path Planning Based on Improved Reinforcement Learning Optimization 基于改进强化学习优化的移动机器人路径规划

Proceedings of the 2019 International Conference on Robotics Systems and Vehicle Technology - RSVT '19 Pub Date : 2019-10-16 DOI: 10.1145/3366715.3366717

Yanshu Jing, Yukun Chen, Ming-hai Jiao, Jie Huang, Bowen Niu, Wenbo Zheng

{"title":"Mobile Robot Path Planning Based on Improved Reinforcement Learning Optimization","authors":"Yanshu Jing, Yukun Chen, Ming-hai Jiao, Jie Huang, Bowen Niu, Wenbo Zheng","doi":"10.1145/3366715.3366717","DOIUrl":"https://doi.org/10.1145/3366715.3366717","url":null,"abstract":"The constant parameter is usually set in adaptive function with traditional mobile robot path planning problem. Q-learning, a type of reinforcement learning, has gained increasing popularity in autonomous mobile robot path recently. In order to effectively solve mobile robot path planning problem in obstacle avoidance environment, a path planning model and search algorithm based on improved reinforcement learning are proposed. The incentive model of reinforcement learning mechanism is introduced with search selection strategy, modifying dynamic reward function parameter setting. The group intelligent search iterative process of global position selection and local position selection is exploited to combine particle behavior with reinforcement learning algorithm, dynamically adjusting the empirical parameter of the reward function by strengthening the data training experiment of Q-learning. to determine the constant parameters for simulation experiment, once the distance between the robot and the obstacle is less than a certain thresholds value, the 0-1 random number is used to randomly adjust the moving direction, avoiding the occurrence of mobile robot path matching deadlock. The study case shows that the proposed algorithm is proved to be better efficient and effective, thereby improving the search intensity and accuracy of the mobile robot path planning problem. And the experimental simulation shows that the proposed model and algorithm effectively solve mobile robot path planning problem that the parameter selection and the actual scene cannot be adapted in real time in traditional path planning problem.","PeriodicalId":425980,"journal":{"name":"Proceedings of the 2019 International Conference on Robotics Systems and Vehicle Technology - RSVT '19","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124945405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Research of PM2.5 Real-Time Prediction Model in Spark Cluster Environment 星火簇环境下PM2.5实时预测模型研究

Proceedings of the 2019 International Conference on Robotics Systems and Vehicle Technology - RSVT '19 Pub Date : 2019-10-16 DOI: 10.1145/3366715.3366722

Lizhi Liu, Jingwei He, Bei Peng, Min Yang, Chenyue Zhang

引用次数: 0