Correction to: Parallel Single-Pixel Imaging: A General Method for Direct–Global Separation and 3D Shape Reconstruction Under Strong Global Illumination

International Journal of Computer Vision - In the original publication of the article, the name of the last author should be Yang Xu, instead of Xu Yang. “Xu” is the family name, and...     

Prediction of highway asphalt pavement performance based on Markov chain and artificial neural network approach

The Journal of Supercomputing - In order to study the problems of inadequate maintenance measures, inappropriate maintenance time, and unreasonable use of funds in asphalt pavement maintenance of...     

From text to graph: a general transition-based AMR parsing using neural network

Neural Computing and Applications - Semantic understanding is an essential research issue for many applications, such as social network analysis, collective intelligence and content computing,...     

Bibliometric analysis on tendency and topics of artificial intelligence over last decade

Microsystem Technologies - Artificial intelligence (AI), together with its applications, has received world-wide attentions and is expected to exert force on the development of global economy and...     

Editorial: Special issue on neural computing and applications in cyber intelligence: ATCI 2020

Neural Computing and Applications -     

Texture compensation with multi-scale dilated residual blocks for image denoising

Neural Computing and Applications - Deep convolutional neural networks have achieved great success for image denoising recently. However, increasing the depth of the neural network cannot...     

EEG extended source imaging with structured sparsity and $$L_1$$ -norm residual

Neural Computing and Applications - It is a long-standing challenge to reconstruct the locations and extents of cortical neural activities from electroencephalogram (EEG) recordings, especially...     

A deep multi-source adaptation transfer network for cross-subject electroencephalogram emotion recognition

Neural Computing and Applications - In real-world application of affective brain–computer interface (aBCI), individual differences across subjects and non-stationary characteristics of...     

基于上下文感知与自适应响应融合的相关滤波跟踪算法

针对当前相关滤波跟踪算法在抗背景干扰、响应融合方式以及模型更新策略上的不足,提出一种基于上下文感知与自适应响应融合的相关滤波跟踪算法.通过引入上下文感知技术,提高算法在背景杂波及遮挡等跟踪场景下的鲁棒性;通过研究HOG特征和颜色直方图特征二者响应图和响应值的特点,提出一种自适应响应融合方法,提升融合响应图的可靠性;在模型更新方面,采用了高置信度模型更新策略来减轻传统模型更新策略中模型污染及跟踪漂移的问题.实验结果表明,本文算法在OTB50数据集上达到了74.7%的跟踪精度,跟踪成功率为54.8%,均优于对比的主流相关滤波跟踪算法,并且在背景杂波、光照变化、遮挡、运动模糊等复杂跟踪场景中具有较好的跟踪精度与鲁棒性.     

命名数据网络中的视频传输研究综述

互联网目前已经发展为一个由实时视频和视频点播等内容分发服务主导的网络.传统IP网络对于视频分发类任务的支持存在组播的部署复杂且开销大,不能有效利用多路径获取内容、对移动性的支持差和难以同时满足可靠性以及低延时需求等问题.命名数据网络(named data networking,NDN)作为新型的下一代互联网体系结构,支持网络内缓存和多路径传输,而且由消费者驱动的传输模式使其天然地支持消费者端移动性.以上特点使NDN具有高效传输视频内容的潜力.首先介绍了视频传输和NDN的基础背景,然后阐述了一些利用NDN中优势实现视频传输的设计方案.通过对已有方案的总结与比较,最后指出了在NDN中传输视频所面临的挑战.