PATTERN RECOGNITION LETTERS

Pattern Recognition Letters aims at rapid publication of concise articles of a broad interest in pattern recognition.Subject areas include all the current fields of interest represented by the Technical Committees of the International Association of Pattern Recognition, and other developing themes involving learning and recognition. Examples include:? Statistical, structural, syntactic pattern recognition;? Neural networks, machine learning, data mining;? Discrete geometry, algebraic, graph-based techniques for pattern recognition;? Signal analysis, image coding and processing, shape and texture analysis;? Computer vision, robotics, remote sensing;? Document processing, text and graphics recognition, digital libraries;? Speech recognition, music analysis, multimedia systems;? Natural language analysis, information retrieval;? Biometrics, biomedical pattern analysis and information systems;? Special hardware architectures, software packages for pattern recognition.We invite contributions as research reports or commentaries.Research reports should be concise summaries of methodological inventions and findings, with strong potential of wide applications.Alternatively, they can describe significant and novel applications of an established technique that are of high reference value to the same application area and other similar areas.Commentaries can be lecture notes, subject reviews, reports on a conference, or debates on critical issues that are of wide interests.To serve the interests of a diverse readership, the introduction should provide a concise summary of the background of the work in an accepted terminology in pattern recognition, state the unique contributions, and discuss broader impacts of the work outside the immediate subject area. All contributions are reviewed on the basis of scientific merits and breadth of potential interests.

PATTERN RECOGNITION LETTERS期刊中文简介

模式识别信函旨在快速出版对模式识别有广泛兴趣的简明文章。主题领域包括由国际模式识别协会技术委员会代表的所有当前感兴趣的领域，以及涉及学习和识别的其他发展主题。示例包括：?统计、结构、句法模式识别；?神经网络、机器学习、数据挖掘；?离散几何、代数、基于图形的模式识别技术；?信号分析、图像编码与处理、形状与纹理分析；?计算机视觉、机器人、遥感；?文档处理、文本和图形识别、数字图书馆；?语音识别、音乐分析、多媒体系统；?自然语言分析、信息检索；?生物统计学、生物医学模式分析和信息系统；?用于模式识别的特殊硬件架构和软件包。我们邀请投稿作为研究报告或评论。研究报告应是方法学发明和发现的简明摘要，具有广泛应用的潜力。或者，它们可以描述已建立的技术的重要和新颖的应用，这些应用对相同的应用领域和其他类似领域具有很高的参考价值。注释可以是课堂讲稿、主题评论、会议报告，也可以是广泛关注的关键问题的辩论。为了满足不同读者的兴趣，引言应该用模式识别中公认的术语对该作品的背景进行简要概述，说明其独特的贡献，并讨论该作品在当前主题领域之外的更广泛的影响。所有的贡献都是根据科学价值和潜在利益的广度来审查的。

中科院SCI期刊分区：

大类学科	分区	小类学科	分区	Top期刊	综述期刊
计算机科学	3区	COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 计算机：人工智能	3区	否	否