基于Transformer的高光谱图像超分辨率重建

高光谱图像超分辨率重建旨在融合高分辨率多光谱图像与低分辨率高光谱图像以得到高分辨率高光谱图像.如何实现二者中空域信息和谱域信息的有效融合是高光谱图像超分辨率重建的关键.受高光谱图像的端元表示模型启发,本文在神经网络中显式地对端元进行建模,并利用其作为纽带实现空域信息和谱域信息的融合.具体来说,本文提出了一个基于Transformer的高光谱图像超分辨率重建网络,利用Transformer结构从低分辨率高光谱图像提取端元信息,并将端元信息融合到高分辨率多光谱图像中,进而完成高分辨率高光谱图像的重建.实验结果表明, Transformer结构的全局感受野增强了网络的长程建模能力,提高了端元提取精度,进而提升了超分辨率重建性能.与已有方法相比,本文所提方法在室内/遥感高光谱数据集上均取得了更优的性能.     

用于单幅模糊图像超分辨的Transformer融合网络

目的 以卷积神经网络为代表的深度学习方法已经在单帧图像超分辨领域取得了丰硕成果,这些方法大多假设低分辨图像不存在模糊效应。然而,由于相机抖动、物体运动等原因,真实场景下的低分辨率图像通常会伴随着模糊现象。因此,为了解决模糊图像的超分辨问题,提出了一种新颖的Transformer融合网络。方法 首先使用去模糊模块和细节纹理特征提取模块分别提取清晰边缘轮廓特征和细节纹理特征。然后,通过多头自注意力机制计算特征图任一局部信息对于全局信息的响应,从而使Transformer融合模块对边缘特征和纹理特征进行全局语义级的特征融合。最后,通过一个高清图像重建模块将融合特征恢复成高分辨率图像。结果 实验在2个公开数据集上与最新的9种方法进行了比较,在GOPRO数据集上进行2倍、4倍、8倍超分辨重建,相比于性能第2的模型GFN(gated fusion network),峰值信噪比(peak signal-to-noive ratio,PSNR)分别提高了0.12 d B、0.18 d B、0.07 d B;在Kohler数据集上进行2倍、4倍、8倍超分辨重建,相比于性能第2的模型GFN,PSNR值分别...     

基于双分支融合的反馈迭代金字塔去模糊和超分辨率算法

针对低分辨率模糊图像实施超分辨率重建后出现大量伪影和边缘纹理不清晰问题,提出了一种双分支融合的反馈迭代金字塔算法.首先采用不同的分支模块分别提取低分辨率模糊图像中潜在的去模糊特征和超分辨率特征信息;然后采用自适应融合机制将两种不同性质的特征进行信息匹配,使网络在去模糊和超分辨率重建模块中更加关注模糊区域;其次使用迭代金字塔重建模块将低分辨率模糊图像渐进重建为逼近真实分布的超分辨率清晰图像;最后重建图像通过分支反馈模块生成清晰低分辨率图像,构建反馈监督.在GOPRO数据集中与现有算法的对比实验结果表明,所提算法能够生成纹理细节更加清晰的超分辨率图像.     

高分辨率可见光图像引导红外图像超分辨率的Transformer网络

目的 红外图像在工业中发挥着重要的作用。但是由于技术原因,红外图像的分辨率一般较低,限制了其普遍适用性。许多低分辨率红外传感器都和高分辨率可见光传感器搭配使用,一种可行的思路是利用可见光传感器捕获的高分辨率图像,辅助红外图像进行超分辨率重建。方法 本文提出了一种使用高分辨率可见光图像引导红外图像进行超分辨率的神经网络模型,包含两个模块：引导Transformer模块和超分辨率重建模块。考虑到红外和可见光图像对一般存在一定的视差,两者之间是不完全对齐的,本文使用基于引导Transformer的信息引导与融合方法,从高分辨率可见光图像中搜索相关纹理信息,并将这些相关纹理信息与低分辨率红外图像的信息融合得到合成特征。然后这个合成特征经过后面的超分辨率重建子网络,得到最终的超分辨率红外图像。在超分辨率重建模块,本文使用通道拆分策略来消除深度模型中的冗余特征,减少计算量,提高模型性能。结果 本文方法在FLIR-aligned数据集上与其他代表性图像超分辨率方法进行对比。实验结果表明,本文方法可以取得优于对比方法的超分辨率性能。客观结果上,本文方法比其他红外图像引导超分辨率方法在峰值信噪比(pea...     

融合迭代反馈与注意力机制的图像超分辨重建方法

针对图像超分辨重建过程中原始高清图片与低质量图像之间缺乏依赖关系、深度网络中特征图信息不分主次重构导致的图像高频信息高精度重构困难的问题,提出一种融合迭代反馈与注意力机制的单幅图像超分辨重建方法。首先使用频率分解模块分别提取图像中的高、低频信息,并将二者分别处理,使网络重点关注提取出的高频细节部分,增强方法在图像细节上的复原能力;其次通过通道注意力机制将重建的重点放在有效特征所在的特征通道上,增强网络提取特征图信息的能力;然后采用迭代反馈的思想,在反复重建和比对过程中增加图像的还原程度;最后通过重建模块生成输出图像。在Set5、Set14、BSD100、Urban100和Manga109基准数据集上的2倍、4倍和8倍放大实验中,与主流超分辨率方法相比,所提方法表现出更优越的性能。在Manga109数据集的8倍放大实验中,相较于传统插值方法和基于卷积神经网络的图像超分辨率算法（SRCNN）,所提方法的峰值信噪比（PSNR）均值分别提升了约3.01 dB和2.32 dB。实验结果表明：所提方法能够降低重建过程中出现的误差,并有效重建出更精细的高分辨率图像。     

基于元上采样的单幅图像任意尺度超分辨率重建

针对传统单幅图像超分辨率深度学习方法将不同尺度低分辨率视作独立任务的问题,提出一种以残差通道注意力模块作为特征提取,元上采样模块作为放大模块的超分辨率网络。残差通道注意力机制可以滤除冗余低频信息减少网络深度,使元上采样模块更好地训练不同尺度低分辨率图像特征间的关系,实现任意尺度的超分辨率网络。为了验证该方法有效性,在Set5、Set14、Urban100等公共数据集上实验。实验结果表明,该方法在整数与非整数倍尺度都能很好地恢复高分辨率图像。     

结合MCycleGAN与RFCNN实现太阳斑点图高分辨重建

太阳斑点图高分辨率重建是天文图像处理的重要研究内容之一.基于深度学习的图像高分辨率重建,通过神经网络模型学习获得低分辨率图像到高分辨率图像的端到端映射函数,能够恢复图像高频信息,但在用于特征单一、噪音较多、局部细节模糊的太阳斑点图重建时,存在边缘过于平滑、高频信息易丢失等不足.将输入图像与重建图像结构特征加入CycleGAN网络中得到MCycleGAN,利用生成器网络从结构特征中获取高频信息,计算特征差来增强网络重建高频信息的能力;将残差块和融合层加入DeepFuse网络中构建RFCNN,利用图像帧间相似信息互补进行多帧重建,使重建图像边缘更加清晰.利用所提方法的重建结果与云南天文台使用的斑点掩膜法Level1+的结果对比表明,所提算法具有误差小、重建图像清晰度高等优点.     

融合参考图像的人脸超分辨率重构方法

基于深度学习的图像超分辨率重构方法对低分辨率人脸图像进行超分辨率重构时,通常存在重构图像模糊和重构图像与真实图像差异较大等问题.基于此问题,文中提出融合参考图像的人脸超分辨率重构方法,可以实现对低分辨率人脸图像的有效重构.参考图像特征提取子网提取参考图像的多尺度特征,保留人脸神态和重点部位的细节特征信息,去除人脸轮廓和面部表情等冗余信息.基于提取的参考图像多尺度特征,逐级超分主网络对低分辨率人脸图像特征进行逐次填充,最终重构生成高分辨率的人脸图像.在数据集上的实验表明,文中方法可以实现对低分辨率人脸图像的有效重构,具有良好的鲁棒性.     

多层次融合注意力网络的双目图像超分辨率重建

目的 随着深度卷积神经网络广泛应用于双目立体图像超分辨率重建任务,双目图像之间的信息融合成为近年来的研究热点。针对目前的双目图像超分辨重建算法对单幅图像的内部信息学习较少的问题,提出多层次融合注意力网络的双目图像超分辨率重建算法,在立体匹配的基础上学习图像内部的丰富信息。方法 首先,利用特征提取模块从不同尺度和深度来获取左图和右图的低频特征。然后,将低频特征作为混合注意力模块的输入,此注意力模块先利用二阶通道非局部注意力模块学习每个图像内部的通道和空间特征,再采用视差注意力模块对左右特征图进行立体匹配。接着采用多层融合模块获取不同深度特征之间的相关信息,进一步指导产生高质量图像重建效果。再利用亚像素卷积对特征图进行上采样,并和低分辨率左图的放大特征相加得到重建特征。最后使用1层卷积得到重建后的高分辨率图像。结果 本文算法采用Flickr1024数据集的800幅图像和60幅经过2倍下采样的Middlebury图像作为训练集,以峰值信噪比（peak signal-to-noise ratio,PSNR）和结构相似性（structural similarity,SSIM）作为指标。实验在3个...     

基于小波域的深度残差网络图像超分辨率算法

单幅图像超分辨率（SISR）是指从一张低分辨率图像重建高分辨率图像.传统的神经网络方法通常在图像的空间域进行超分辨率重构，但这些方法常在重构过程中忽略重要的细节.鉴于小波变换能够将图像内容的"粗略"和"细节"特征进行分离，提出一种基于小波域的深度残差网络（DRWSR）.不同于其他传统的卷积神经网络直接推导高分辨率图像（HR），该方法采用多阶段学习策略，首先推理出高分辨率图像对应的小波系数，然后重建超分辨率图像（SR）.为了获取更多的信息，该方法采用一种残差嵌套残差的灵活可扩展的深度神经网络.此外，提出的神经网络模型采用结合图像空域与小波域的损失函数进行优化求解.所提出的方法在Set5、Set14、BSD100、Urban100等数据集上进行实验，实验结果表明，该方法的视觉效果和峰值信噪比（PSNR）均优于相关的图像超分辨率方法.     

Only connect: teaching, technology and telesis

Abstract This paper describes an approach to the design of interactive multimedia materials being developed in a European Community project. The developmental process is seen as a dialogue between technologists and teachers. This dialogue is often problematic because of the differences in training, experience and culture between them. Conditions needed for fruitful dialogue are described and the generic model for learning design used in the project is explained.     

European Community policy and the market

Abstract This paper starts with some reflections on the policy considerations and priorities which are shaping European Commission (EC) research programmes. Then it attempts to position the current projects which seek to capitalise on information and communications technologies for learning in relation to these priorities and the apparent realities of the marketplace. It concludes that while there are grounds to be optimistic about the contribution EC programmes can make to the efficiency and standard of education and training, they are still too technology driven.     

一种自适应子融合集成多分类器方法

融合集成方法已经广泛应用在模式识别领域,然而一些基分类器实时性能稳定性较差,导致多分类器融合性能差,针对上述问题本文提出了一种新的基于多分类器的子融合集成分类器系统。该方法考虑在度量层融合层次之上通过对各类基多分类器进行动态选择,票数最多的类别作为融合系统中对特征向量识别的类别,构成一种新的自适应子融合集成分类器方法。实验表明,该方法比传统的分类器以及分类融合方法识别准确率明显更高,具有更好的鲁棒性。     

Avoiding semantic and temporal gaps in developing software intensive systems

Development of software intensive systems (systems) in practice involves a series of self-contained phases for the lifecycle of a system. Semantic and temporal gaps, which occur among phases and among developer disciplines within and across phases, hinder the ongoing development of a system because of the interdependencies among phases and among disciplines. Such gaps are magnified among systems that are developed at different times by different development teams, which may limit reuse of artifacts of systems development and interoperability among the systems. This article discusses such gaps and a systems development process for avoiding them.     

Designing economic np control charts: A programmed simulation approach

This paper presents control charts models and the necessary simulation software for the location of economic values of the control parameters. The simulation program is written in FORTRAN, requires only 10K of main storage, and can run on most mini and micro computers. Two models are presented - one describes the process when it is operating at full capacity and the other when the process is operating under capacity. The models allow the product quality to deteriorate to a further level before an existing out-of-control state is detected, and they can also be used in situations where no prior knowledge exists of the out-of-control causes and the resulting proportion defectives.     

The development of robot art

Going through a few examples of robot artists who are recognized worldwide, we try to analyze the deepest meaning of what is called “robot art” and the related art field definition. We also try to highlight its well-marked borders, such as kinetic sculptures, kinetic art, cyber art, and cyberpunk. A brief excursion into the importance of the context, the message, and its semiotics is also provided, case by case, together with a few hints on the history of this discipline in the light of an artistic perspective. Therefore, the aim of this article is to try to summarize the main characteristics that might classify robot art as a unique and innovative discipline, and to track down some of the principles by which a robotic artifact can or cannot be considered an art piece in terms of social, cultural, and strictly artistic interest. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Explanation and prediction: an architecture for default and abductive reasoning

Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given.     

Three Process Perspectives: Organizations, Teams, and People

This paper provides the author's personal views and perspectives on software process improvement. Starting with his first work on technology assessment in IBM over 20 years ago, Watts Humphrey describes the process improvement work he has been directly involved in. This includes the development of the early process assessment methods, the original design of the CMM, and the introduction of the Personal Software Process (PSP)^SM and Team Software Process (TSP){^SM}. In addition to describing the original motivation for this work, the author also reviews many of the problems he and his associates encountered and why they solved them the way they did. He also comments on the outstanding issues and likely directions for future work. Finally, this work has built on the experiences and contributions of many people. Mr. Humphrey only describes work that he was personally involved in and he names many of the key contributors. However, so many people have been involved in this work that a full list of the important participants would be impractical.     

基于复小波噪声方差显著修正的SAR图像去噪

提出了一种基于复小波域统计建模与噪声方差估计显著性修正相结合的合成孔径雷达(Synthetic Aperture Radar,SAR)图像斑点噪声滤波方法。该方法首先通过对数变换将乘性噪声模型转化为加性噪声模型,然后对变换后的图像进行双树复小波变换(Dualtree Complex Wavelet Transform,DCWT),并对复数小波系数的统计分布进行建模。在此先验分布的基础上,通过运用贝叶斯估计方法从含噪系数中恢复原始系数,达到滤除噪声的目的。实验结果表明该方法在去除噪声的同时保留了图像的细节信息,取得了很好的降噪效果。     

How do children do mathematics with LOGO?

Abstract  This paper considers some results of a study designed to investigate the kinds of mathematical activity undertaken by children (aged between 8 and 11) as they learned to program in LOGO. A model of learning modes is proposed, which attempts to describe the ways in which children used and acquired understanding of the programming/mathematical concepts involved. The remainder of the paper is concerned with discussing the validity and limitations of the model, and its implications for further research and curriculum development.