城市POI的分布情况客观反映了一个城市各行各业的发展情况,传统获取POI的测绘手段成本高、更新周期长、时效性差,而基于位置的社交网络(Location-Based Social Network,LBSN)平台的发展为实现城市POI的感知提供了一种新思路。本文提出...城市POI的分布情况客观反映了一个城市各行各业的发展情况,传统获取POI的测绘手段成本高、更新周期长、时效性差,而基于位置的社交网络(Location-Based Social Network,LBSN)平台的发展为实现城市POI的感知提供了一种新思路。本文提出一种基于LBSN数据聚类分析的城市POI感知方法,首先,对LBSN数据进行预处理,包括清洗重复数据、删除无效数据、数据预分类等,以提高数据的有效性;其次,提出一种改进的DBSCAN算法,对处理后的数据进行聚类分析,从而得到准确度较高的城市各类POI分布情况。实验结果表明,与传统的DBSCAN算法以及K-means算法相比,本文提出的算法有更好的聚类效果,且在聚类指标上有更大的CH指数值和更小的DBI指数值。展开更多
图像重建是光学计算成像的关键环节之一。目前基于深度学习的图像重建主要使用卷积神经网络、循环神经网络或生成对抗网络等模型。大多数研究仅通过单一模态的数据训练模型,难以在保证成像质量的同时又具备不同场景的泛化能力。为解决...图像重建是光学计算成像的关键环节之一。目前基于深度学习的图像重建主要使用卷积神经网络、循环神经网络或生成对抗网络等模型。大多数研究仅通过单一模态的数据训练模型,难以在保证成像质量的同时又具备不同场景的泛化能力。为解决这一问题,提出了一种基于Transformer模块的多模态图像重建模型(multi-modal image reconstruction model based on the Transformer,Trans-MIR)。实验结果表明,Trans-MIR能够从多模态数据中提取图像特征,实现高质量的图像重建,对二维通用人脸散斑图像进行图像重建的结构相似度高达0.93,对三维微管结构图像的超分辨重建的均方误差低至10^(−4)量级。Trans-MIR对研究多模态图像重建具有一定的启发作用。展开更多
Semantic Communication(SC)has emerged as a novel communication paradigm that provides a receiver with meaningful information extracted from the source to maximize information transmission throughput in wireless networ...Semantic Communication(SC)has emerged as a novel communication paradigm that provides a receiver with meaningful information extracted from the source to maximize information transmission throughput in wireless networks,beyond the theoretical capacity limit.Despite the extensive research on SC,there is a lack of comprehensive survey on technologies,solutions,applications,and challenges for SC.In this article,the development of SC is first reviewed and its characteristics,architecture,and advantages are summarized.Next,key technologies such as semantic extraction,semantic encoding,and semantic segmentation are discussed and their corresponding solutions in terms of efficiency,robustness,adaptability,and reliability are summarized.Applications of SC to UAV communication,remote image sensing and fusion,intelligent transportation,and healthcare are also presented and their strategies are summarized.Finally,some challenges and future research directions are presented to provide guidance for further research of SC.展开更多
文摘城市POI的分布情况客观反映了一个城市各行各业的发展情况,传统获取POI的测绘手段成本高、更新周期长、时效性差,而基于位置的社交网络(Location-Based Social Network,LBSN)平台的发展为实现城市POI的感知提供了一种新思路。本文提出一种基于LBSN数据聚类分析的城市POI感知方法,首先,对LBSN数据进行预处理,包括清洗重复数据、删除无效数据、数据预分类等,以提高数据的有效性;其次,提出一种改进的DBSCAN算法,对处理后的数据进行聚类分析,从而得到准确度较高的城市各类POI分布情况。实验结果表明,与传统的DBSCAN算法以及K-means算法相比,本文提出的算法有更好的聚类效果,且在聚类指标上有更大的CH指数值和更小的DBI指数值。
文摘图像重建是光学计算成像的关键环节之一。目前基于深度学习的图像重建主要使用卷积神经网络、循环神经网络或生成对抗网络等模型。大多数研究仅通过单一模态的数据训练模型,难以在保证成像质量的同时又具备不同场景的泛化能力。为解决这一问题,提出了一种基于Transformer模块的多模态图像重建模型(multi-modal image reconstruction model based on the Transformer,Trans-MIR)。实验结果表明,Trans-MIR能够从多模态数据中提取图像特征,实现高质量的图像重建,对二维通用人脸散斑图像进行图像重建的结构相似度高达0.93,对三维微管结构图像的超分辨重建的均方误差低至10^(−4)量级。Trans-MIR对研究多模态图像重建具有一定的启发作用。
基金supported by the Natural Science Foundation of China under Grants 61971084,62025105,62001073,62272075the National Natural Science Foundation of Chongqing under Grants cstc2021ycjh-bgzxm0039,cstc2021jcyj-msxmX0031+1 种基金the Science and Technology Research Program for Chongqing Municipal Education Commission KJZD-M202200601the Support Program for Overseas Students to Return to China for Entrepreneurship and Innovation under Grants cx2021003,cx2021053.
文摘Semantic Communication(SC)has emerged as a novel communication paradigm that provides a receiver with meaningful information extracted from the source to maximize information transmission throughput in wireless networks,beyond the theoretical capacity limit.Despite the extensive research on SC,there is a lack of comprehensive survey on technologies,solutions,applications,and challenges for SC.In this article,the development of SC is first reviewed and its characteristics,architecture,and advantages are summarized.Next,key technologies such as semantic extraction,semantic encoding,and semantic segmentation are discussed and their corresponding solutions in terms of efficiency,robustness,adaptability,and reliability are summarized.Applications of SC to UAV communication,remote image sensing and fusion,intelligent transportation,and healthcare are also presented and their strategies are summarized.Finally,some challenges and future research directions are presented to provide guidance for further research of SC.
