一种利用多传感器进行目标识别的方法

针对传统单传感器目标识别利用目标信息有限、识别结果可靠性不高等缺陷 ,提出一种利用多传感器进行目标识别方法 ,这种方法充分利用了目标多重特征的信息 ,并考虑了不同特征信息在目标识别中的重要程度 ,从而得到更为接近实际效果的识别结果     

Irreducible constituents of monomial representations

We describe an algorithm for obtaining the central primitive idempotents of the algebra associated with a monomial representation. As a consequence, we obtain its irreducible constituents. This is implemented in Magma, using an algorithm based on Dixon’s modular approach. In the case of permutation representations, we get a simplified version of the algorithms of Michler and Weller.     

A Dialectal Chinese Speech Recognition Framework

A framework for dialectal Chinese speech recognition is proposed and studied, in which a relatively small dialectal Chinese (or in other words Chinese influenced by the native dialect) speech corpus and dialect-related knowledge are adopted to transform a standard Chinese (or Putonghua, abbreviated as PTH) speech recognizer into a dialectal Chinese speech recognizer. Two kinds of knowledge sources are explored: one is expert knowledge and the other is a small dialectal Chinese corpus. These knowledge sources provide information at four levels: phonetic level, lexicon level, language level, and acoustic decoder level. This paper takes Wu dialectal Chinese (WDC) as an example target language. The goal is to establish a WDC speech recognizer from an existing PTH speech recognizer based on the Initial-Final structure of the Chinese language and a study of how dialectal Chinese speakers speak Putonghua. The authors propose to use context-independent PTH-IF mappings (where IF means either a Chinese Initial or a Chinese Final), context-independent WDC-IF mappings, and syllable-dependent WDC-IF mappings (obtained from either experts or data), and combine them with the supervised maximum likelihood linear regression (MLLR) acoustic model adaptation method. To reduce the size of the multi-pronunciation lexicon introduced by the IF mappings, which might also enlarge the lexicon confusion and hence lead to the performance degradation, a Multi-Pronunciation Expansion (MPE) method based on the accumulated uni-gram probability (AUP) is proposed. In addition, some commonly used WDC words are selected and added to the lexicon. Compared with the original PTH speech recognizer, the resulting WDC speech recognizer achieves 10-18% absolute Character Error Rate (CER) reduction when recognizing WDC, with only a 0.62% CER increase when recognizing PTH. The proposed framework and methods are expected to work not only for Wu dialectal Chinese but also for other dialectal Chinese languages and even other languages.     

模式识别技术对Al_2O_3-TiC-ZrO_2纳米复合材料制备工艺参数的优化和预报

利用燃烧合成 热压工艺制备Al2 O3 TiC ZrO2 纳米复合材料 ,利用计算机模式识别技术中的非线性映照对其工艺参数进行分析。以陶瓷的抗弯强度和断裂韧性作为判据 ,给出参数目标优化区域。采用非线性逆映照研究不同工艺参数对材料性能的影响趋势 ,并对工艺参数进行预报和设计 ,再用实验结果予以验证 ,克服了传统“炒菜式”合成方法的盲目性。     

DRS航管雷达模拟机自动机长语音技术研究

随着DRS航管雷达模拟机广泛应用于民航管制训练中,研制采用语音识别和合成技术的自动机长势在必行。就语音识别技术在DRS航管雷达模拟机中的应用进行了研究和试验,并给出了基于IBM Voice Type的具体实现。实践证明,这一方案是可行的,而且效果比较理想。     

基于神经网络的汽车牌照提取研究

汽车牌照的提取是牌照识别的前提,本文主要采用BP神经网络在灰度图像中提取汽车牌照。算法包括在个部分：神经网络的训练,图像的预处理,用训练出的神经网络来提取汽车牌照。     

基于在线识别的机器人动态手眼协调

本文研究了基于在线识别的机器人动态手眼协调,通过视觉在线识别目标的结果来 动态规划机器人的运动,改善了系统的柔性,提高了系统对环境的适应能力．实验证明,文 中所采用的识别算法具有很好的实时性和可靠性．引入语音控制改善了人机交互．     

基于模糊理论的地面三维目标识别方法

本文就模糊理论在模式识别领域中的应用 ,对地面三维目标进行模糊模式识别的实现做了一些研究工作 .利用成熟的二维图像识别技术与多对一模型和目标类型建库方法的结合 ,完成对三维目标的识别     

Spatial interest pixels (SIPs): useful low-level features of visual media data

Visual media data such as an image is the raw data representation for many important applications. Reducing the dimensionality of raw visual media data is desirable since high dimensionality degrades not only the effectiveness but also the efficiency of visual recognition algorithms. We present a comparative study on spatial interest pixels (SIPs), including eight-way (a novel SIP detector), Harris, and Lucas‐Kanade, whose extraction is considered as an important step in reducing the dimensionality of visual media data. With extensive case studies, we have shown the usefulness of SIPs as low-level features of visual media data. A class-preserving dimension reduction algorithm (using GSVD) is applied to further reduce the dimension of feature vectors based on SIPs. The experiments showed its superiority over PCA.

Sisl: Several Interfaces, Single Logic

Modern interactive services such as information and e-commerce services are becoming increasingly more flexible in the types of user interfaces they support. These interfaces incorporate automatic speech recognition and natural language understanding and include graphical user interfaces on the desktop and web-based interfaces using applets and HTML forms. To what extent can the user interface software be decoupled from the service logic software (the code that defines the essential function of a service)? Decoupling of user interface from service logic directly impacts the flexibility of services, or how easy they are to modify and extend. To explore these issues, we have developed Sisl, an architecture and domain-specific language for designing and implementing interactive services with multiple user interfaces. A key principle underlying Sisl is that all user interfaces to a service share the same service logic. Sisl provides a clean separation between the service logic and the software for a variety of interfaces, including Java applets, HTML pages, speech-based natural language dialogue, and telephone-based voice access. Sisl uses an event-based model of services that allows service providers to support interchangeable user interfaces (or add new ones) to a single consistent source of service logic and data. As part of a collaboration between research and development, Sisl is being used to prototype a new generation of call processing services for a Lucent Technologies switching product.