A Multi-View Face Recognition System

In many automatic face recognition systems,posture constraining is a key factor preventing them from application.In this paper a series of strategies will be described to achieve a system which enables face recognition under varying pose.These approaches include the multi-view face modeling,the threschold image based face feature detection,the affine transformation based face posture normalization and the template matching based face identification.Combining all of these strategies,a face recognition system with the pose invariance is designed successfully,Using a 75MHZ Pentium PC and with a database of 75 individuals,15 images for each person,and 225 test images with various postures,a very good recognition rate of 96.89% is obtained.     

Martha J. Farah.

Recognizes Martha J. Farah for rigorous empirical and theoretical analysis of visual cognition, in which understanding of normal function and analysis of neurological deficits illuminate and strengthen one another. Applying diverse experimental techniques within an integrated approach to the study of mind and brain, she has sharpened and helped to answer fundamental questions about how humans generate and manipulate visual images, recognize objects, and attend to positions in space. Along with a citation, a biography is presented for Farah, as well as a bibliography of her works. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

连续语音识别系统性能评估软件

本文介绍了以一种比较两个句子的新的有效算法为基础而编制的连续语音识别系统性能评估软件，它通过比较连续语音识别系统输出的若干句子和相应的标准句子，得到系统性能的定量数据。该软件的可靠性得到大量实验验证。     

基于极化不变量的飞机目标识别

基于宽带毫米波极化雷达体制背影，通过极化不变量之一的去极化系数，研究了飞机目标的极化散射特性，并提取了极化特征，设计了飞机目标的分类或识别器结构，它能对五种飞机目标进行有效的分类或识别。     

实用语音传感器

介绍了利用MCS-96单片计算机构成实用语音传感器的电路设计方案和配合该系统研究的语音识别方法以及实验结果等。     

Word recognition: From letters to meaning.

Reviews the book, Basic Processes in Reading Visual Word Recognition by Derek Besner and Glyn W. Humphreys (see record 1990-99017-000). While there has been an increase in the amount of work on many different aspects of reading, as Besner and Humphreys point out in the overview to their book, the vast majority of the research on the topic of reading in the past twenty years has been concerned with the processes involved in word recognition. For this reason, Besner and Humphreys have attempted to bring together studies on topics which are both relevant to current debates in the field of word recognition, and which are likely to be important for future developments in the field. They have compiled an edited volume consisting of their overview and eight additional chapters. The editors have attempted to span the continuum of processes involved in word recognition and thus have included chapters which cover topics ranging from the visual analysis of words, to those on the influence of semantic factors on word recognition. The authors of these chapters comprise an impressive list of researchers in the field of word recognition, with the majority of chapters being authored by leading researchers on the topic. Given the stature of the authors and the range of topics covered, in theory this volume should provide a very thorough overview of current theory and research on reading. There is no question that each of the chapters is interesting and important in its own right. However, in practice the volume as a whole fell somewhat short of my expectations. The different tacts taken by different authors has resulted in a very uneven coverage of the current debates in the field. Notwithstanding these criticisms, I am sure that the majority of researchers in this field will consider this volume to be an important contribution. The book would provide a very useful addition to graduate courses in cognitive sciences and as a supplemental text for an undergraduate course on the psychology of reading. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Learning-based dynamic coupling of discrete and continuous trackers

We present a data-driven dynamic coupling between discrete and continuous methods for tracking objects of high dofs, which overcomes the limitations of previous techniques. In our approach, two trackers work in parallel, and the coupling between them is based on the tracking error. We use a model-based continuous method to achieve accurate results and, in cases of failure, we re-initialize the model using our discrete tracker. This method maintains the accuracy of a more tightly coupled system, while increasing its efficiency. At any given frame, our discrete tracker uses the current and several previous frames to search into a database for the best matching solution. For improved robustness, object configuration sequences, rather than single configurations, are stored in the database. We apply our framework to the problem of 3D hand tracking from image sequences and the discrimination between fingerspelling and continuous signs in American Sign Language.     

基于小波熵的电容器扰动识别和定位

对投电容器扰动识别和定位的方法进行了改进。针对其他此类方法的不足，比如在电压幅值低时投电容器扰动的识别、定位“可信度不高”等，文中通过提取小波变换的特定层的系数，对需要识别的电容器扰动的分解信号相对增强，而其他扰动的分解信号相对减弱，然后再提取熵特征值，结果表明它可以作为识别低电压时投电容器扰动的依据。在对电容器扰动进行定位时，参考了功率和能量定位法，并对其进行了改进。仿真分析证明，在电压幅值较低时，可以准确和可靠地对电容器扰动进行识别和定位。     

On the dynamic nature of response criterion in recognition memory: Effects of base rate, awareness, and feedback.

The authors examined whether participants can shift their criterion for recognition decisions in response to the probability that an item was previously studied. Participants in 3 experiments were given recognition tests in which the probability that an item was studied was correlated with its location during the test. Results from all 3 experiments indicated that participants' response criteria were sensitive to the probability that an item was previously studied and that shifts in criterion were robust. In addition, awareness of the bases for criterion shifts and feedback on performance were key factors contributing to the observed shifts in decision criteria. These data suggest that decision processes can operate in a dynamic fashion, shifting from item to item. (PsycINFO Database Record (c) 2010 APA, all rights reserved)