Neural Networks, Information and Communication Engineering最新文献_第2页

RiverMapper: step-wisely mapping the surface rivers on optical remote sensing images RiverMapper:在光学遥感图像上逐步绘制地表河流

Neural Networks, Information and Communication Engineering Pub Date : 2022-06-30 DOI: 10.1117/12.2639214

Peng Zhang, H. Pan, Ke Yang, Yong Dou, Xin Niu

{"title":"RiverMapper: step-wisely mapping the surface rivers on optical remote sensing images","authors":"Peng Zhang, H. Pan, Ke Yang, Yong Dou, Xin Niu","doi":"10.1117/12.2639214","DOIUrl":"https://doi.org/10.1117/12.2639214","url":null,"abstract":"Accurately mapping the surface rivers is important in ecological environment monitoring and disaster prevention. The development of remote sensing technology and computer vision greatly improves the efficiency of this task. However, there are few methods that map the rivers from an image directly. The existing automatic river mapping methods usually had two successive stages: waterbody extraction and flow-path extraction, where the latter methods were very dependent on the waterbody masks generated by the former methods. Errors in waterbody masks caused breaks and redundancies in the extracted graphs. This paper proposed RiverMapper, which mapped the rivers step-wisely without dividing into two stages. Following the directions and actions predicted by the convolution neural network, RiverMapper walked along the rivers step by step and cropped the fixed-size image patches at each step for segmentation. Final river graphs were constructed by the waterbody mask patches and those tracks generated by RiverMapper. We applied RiverMapper on optical remote sensing images containing the Changjiang River and the Huanghe River. Without the degradation of the performance on waterbody extraction, RiverMapper outperformed other methods in terms of the local topological and geometrical similarity between the predicted and the ground-truth river graphs.","PeriodicalId":336892,"journal":{"name":"Neural Networks, Information and Communication Engineering","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128989534","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

An optimized digital delay structure for wideband signal transmitting 一种用于宽带信号传输的优化数字延迟结构

Neural Networks, Information and Communication Engineering Pub Date : 2022-06-30 DOI: 10.1117/12.2639122

Wendong Li, Biying Jiang, Yao Deng, Yao Li, Xingchen Lu

引用次数: 0

Porosity prediction of carbonate reservoir based on neural network 基于神经网络的碳酸盐岩储层孔隙度预测

Neural Networks, Information and Communication Engineering Pub Date : 2022-06-30 DOI: 10.1117/12.2640460

Liyan Yang, Xiangdong Peng

{"title":"Porosity prediction of carbonate reservoir based on neural network","authors":"Liyan Yang, Xiangdong Peng","doi":"10.1117/12.2640460","DOIUrl":"https://doi.org/10.1117/12.2640460","url":null,"abstract":"Porosity, as one of the important reservoir physical parameters, plays an important role in reservoir evaluation. Considering the actual work needs, finding a low-cost and efficient method to obtain high-precision porosity has become an important topic of reservoir evaluation. Due to the complex nonlinear mapping relationship and timing characteristics between logging parameters and porosity, a model of deep learning is proposed to predict the porosity of carbonate reservoir according to the existing logging data. Firstly, on the basis of core analysis and geological and logging data, data preprocessing is carried out for carbonate reservoir logging data, including core depth homing, logging data standardization and normalization. The second step is to establish the prediction model of reservoir parameters by using proper learning samples. The third step is to evaluate the predicted effect of porosity model and modify the model by using superposition diagram method and error statistics method. The calculation demerit of the final model is compared with the traditional results.The comparison results in the last step show that the prediction results of reservoir parameters by neural network are more accurate than those by traditional methods.","PeriodicalId":336892,"journal":{"name":"Neural Networks, Information and Communication Engineering","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124209173","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

BTMC-CSMA protocol analysis with handshake mechanism in wireless Ad Hoc network 无线Ad Hoc网络中带握手机制的BTMC-CSMA协议分析

Neural Networks, Information and Communication Engineering Pub Date : 2022-06-30 DOI: 10.1117/12.2639648

Jianjun Hao

引用次数: 0

Research on equipment performance index evaluation system for HPLC 高效液相色谱设备性能指标评价体系研究

Neural Networks, Information and Communication Engineering Pub Date : 2022-06-30 DOI: 10.1117/12.2639328

Zhan Shi, Yutu Liang, Bo Li, Xingnan Li, Xiaozhi Deng, Jiangang Lu

引用次数: 0

A low power consumer capacitor-less low dropout regulator with super class AB CMOS OTA 具有超AB级CMOS OTA的低功耗无电容低差稳压器

Neural Networks, Information and Communication Engineering Pub Date : 2022-06-30 DOI: 10.1117/12.2639174

Shengming Huang, Yu-Min Mu, Xiaocha Wang

引用次数: 0

Design and realization of non-contact electrostatic potential test device 非接触式静电电位测试装置的设计与实现

Neural Networks, Information and Communication Engineering Pub Date : 2022-06-30 DOI: 10.1117/12.2640686

Yi-yong Lin, Z. Xu, T. Song, Mei Zhao, Yibei Chen

引用次数: 0

Design of intelligent scheduling system for IT operation and maintenance services considering task duration 考虑任务时长的IT运维服务智能调度系统设计

Neural Networks, Information and Communication Engineering Pub Date : 2022-06-30 DOI: 10.1117/12.2639380

Haitao Zhang, Xuyong Wang

{"title":"Design of intelligent scheduling system for IT operation and maintenance services considering task duration","authors":"Haitao Zhang, Xuyong Wang","doi":"10.1117/12.2639380","DOIUrl":"https://doi.org/10.1117/12.2639380","url":null,"abstract":"Aiming at the high cost of existing IT operation and maintenance services, an intelligent scheduling system based on task duration was designed. By studying the separable task scheduling in a homogeneous system environment, for a homogeneous star network, comparative analysis of the relationship between the busy state to the idle state, the continuous transmission of transmission tasks, the release time of mixed timing constraints and the time of receiving tasks, is used to This builds a separable task scheduling model. The genetic algorithm is used to optimally solve the scheduling model. Considering the existence and universality of heterogeneous platforms in the actual parallel and distributed system environment, the task scheduling situation of the processor in the heterogeneous star network environment is researched and analyzed. . According to the mixed timing constraints, a task scheduling optimization model in a heterogeneous system environment is constructed, and the genetic algorithm is improved to solve the problem. Due to the enlargement of the problem search space, the local search operator is used to converge the algorithm. The results show that compared with several existing scheduling algorithms, the algorithm proposed in this paper can obtain a better scheduling scheme, so the designed intelligent scheduling system is practical.","PeriodicalId":336892,"journal":{"name":"Neural Networks, Information and Communication Engineering","volume":"12258 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131265958","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 optimization of PAPR reduction in the OFDM-IM system OFDM-IM系统中减小PAPR的优化

Neural Networks, Information and Communication Engineering Pub Date : 2022-06-30 DOI: 10.1117/12.2640509

Xing Ma

引用次数: 1

PNCF: neural collaborative filtering based on pre-trained embedding PNCF:基于预训练嵌入的神经协同过滤

Neural Networks, Information and Communication Engineering Pub Date : 2022-06-30 DOI: 10.1117/12.2639163

Jianqi Pan, M. Yamamura, Atsushi Yoshikawa

引用次数: 0