2020 IEEE 3rd International Conference on Computer and Communication Engineering Technology (CCET)最新文献_第7页

A Method of Motor Imagery EEG Recognition Based on CNN-ELM 基于CNN-ELM的运动图像脑电识别方法

2020 IEEE 3rd International Conference on Computer and Communication Engineering Technology (CCET) Pub Date : 2020-08-01 DOI: 10.1109/CCET50901.2020.9213132

Chunting Song, Yong Sheng

引用次数: 1

An SDN-Based Space-Air-Ground Integrated Network Architecture and Controller Deployment Strategy 基于sdn的天空地一体化网络体系结构及控制器部署策略

2020 IEEE 3rd International Conference on Computer and Communication Engineering Technology (CCET) Pub Date : 2020-08-01 DOI: 10.1109/CCET50901.2020.9213109

Hua Qu, Xiaoyun Xu, Ji-hong Zhao, Pengcheng Yue

引用次数: 14

BIVS: Block Image and Voting Strategy for Weather Image Classification BIVS:用于天气图像分类的块图像和投票策略

2020 IEEE 3rd International Conference on Computer and Communication Engineering Technology (CCET) Pub Date : 2020-08-01 DOI: 10.1109/CCET50901.2020.9213173

Run Ye, B. Yan, Junhua Mi

引用次数: 1

Skeleton-Based Sleep Posture Recognition with BP Neural Network 基于骨骼的BP神经网络睡眠姿势识别

2020 IEEE 3rd International Conference on Computer and Communication Engineering Technology (CCET) Pub Date : 2020-08-01 DOI: 10.1109/CCET50901.2020.9213125

Haozhou Lyu, Jinglan Tian

引用次数: 3

Application of Wireless Communication Technology in Ubiquitous Power Internet of Things 无线通信技术在泛在电力物联网中的应用

2020 IEEE 3rd International Conference on Computer and Communication Engineering Technology (CCET) Pub Date : 2020-08-01 DOI: 10.1109/CCET50901.2020.9213170

Le Ma, Wenhui Li, Yuting Hou, Wenhao Zhan, Rong Yang, W. Jia, Yinghui Qiu

{"title":"Application of Wireless Communication Technology in Ubiquitous Power Internet of Things","authors":"Le Ma, Wenhui Li, Yuting Hou, Wenhao Zhan, Rong Yang, W. Jia, Yinghui Qiu","doi":"10.1109/CCET50901.2020.9213170","DOIUrl":"https://doi.org/10.1109/CCET50901.2020.9213170","url":null,"abstract":"With the rapid development of the economy, various types of distributed energy are continuously connected to the power system, resulting in the increasing pressure of energy supply in the power system, which poses unprecedented challenges to the operation, management, and service of State Grid Corporation. Therefore, State Grid Corporation of China has put forward the strategic goal of building ubiquitous power Internet of things (IoT). As an important part of supporting the construction of a strong smart grid and energy Internet, building ubiquitous power IoT is very important to promote the national energy structure reform, realize the intelligent coordination and optimization of source network load storage, and improve the user energy experience. Wireless communication technology provides channel guarantee for the future end-to-end ubiquitous IoT. This paper first introduces the concept and system composition of ubiquitous IoT and then focuses on the application and development of wireless communication technology including LTE power wireless private network and 5G communication in ubiquitous IoT. Finally, it summarizes the challenges and future development direction of ubiquitous power IoT construction.","PeriodicalId":236862,"journal":{"name":"2020 IEEE 3rd International Conference on Computer and Communication Engineering Technology (CCET)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132501013","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: 6

Transfer Learning Based Fruits Image Segmentation for Fruit-Picking Robots 基于迁移学习的摘果机器人水果图像分割

2020 IEEE 3rd International Conference on Computer and Communication Engineering Technology (CCET) Pub Date : 2020-04-23 DOI: 10.1109/CCET50901.2020.9213127

Yongfu He, Fangfang Pan, Baoyu Wang, Ziqing Teng, Jianhua Wu

{"title":"Transfer Learning Based Fruits Image Segmentation for Fruit-Picking Robots","authors":"Yongfu He, Fangfang Pan, Baoyu Wang, Ziqing Teng, Jianhua Wu","doi":"10.1109/CCET50901.2020.9213127","DOIUrl":"https://doi.org/10.1109/CCET50901.2020.9213127","url":null,"abstract":"It is an important prerequisite for a fruit-picking robot to accurately segment and locate the object in fruit images. However, image segmentation by manually selected features or deep learning-based approaches is a troublesome task. It requires a long time and a large number of annotated images for the model to be trained. In this study, transfer learning is used so that the learned parameters of a pre-trained convolutional neural network can be used as the initial settings in the new task. Three networks, Mobilenet_v2, Resnet_v1_50_beta and Xception_65, are used as backbone networks, which were used in the well-known semantic image segmentation model—DeepLab. The proposed transfer learning-based fruits image segmentation not only alleviates the stringent need of a large image dataset, but also saves much time for training. Experimental results show that the Xception_65 based network has the best performance in terms of the segmentation metric of mean intersection over union. A high-precision instance fruits segmentation guarantees subsequent accurate locations of fruit images for fruit-picking robots, which is of great significance for intelligent agriculture.","PeriodicalId":236862,"journal":{"name":"2020 IEEE 3rd International Conference on Computer and Communication Engineering Technology (CCET)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123002317","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

Robot Path Planning Method Based on Deep Reinforcement Learning 基于深度强化学习的机器人路径规划方法

2020 IEEE 3rd International Conference on Computer and Communication Engineering Technology (CCET) Pub Date : 2020-04-10 DOI: 10.1109/CCET50901.2020.9213166

Yongmei Zhang, Jiarui Zhao, Jie Sun

引用次数: 4