人工神经网络在植被遥感影像分类中的应用研究

比起传统的统计方法，人工神经网络具有很好的非线性处理和并行计算能力，在植被遥感信息处理中得到广泛的应用。本研究系统地介绍了人工神经网络理论及其在植被遥感信息处理中的应用现状。并就如何提高人工神经网络的相干被遥感影像的分类能力进行了详细研究。首次提出了结合植被指数和组成分分析的神经网络分类方法。过去这方面的研究工作大都集中在通过选择一个合适的神经网络模型来提高植被分类精度，而我们认为：根据植被遥感自身的规律，结合统计方法，确定合适的网络输入模式的特征变量，也可以提高分类精度。 研究结果表明，尽管一般的神经网络分类器不需要对输入的模式做明显的特征提取，网络的隐层就具有特征提取的功能。但对TM影像七个波段和常用的五个植被指数（PVI、NDVI、WDVI、PVI、MSAVI2），分别做主成分分析，从而获得人工神经网络输入的特征变量，使用这样一种结合VI、PCA的神经网络对遥感TM多波段影像进行植被分类，能大大提高分类的精度。

Real time feature-based facial tracking using Lie algebras

We have developed a novel human facial tracking system that operates in real time at a video frame rate without needing any special hardware. The approach is based on the use of Lie algebra, and uses three-dimensional feature points on the targeted human face. It is assumed that the roughly estimated facial model (relative coordinates of the three-dimensional feature points) is known. First, the initial feature positions of the face are determined using a model fitting technique. Then, the tracking is operated by the following sequence: (1) capture the new video frame and render feature points to the image plane; (2) search for new positions of the feature points on the image plane; (3) get the Euclidean matrix from the moving vector and the three-dimensional information for the points; and (4) rotate and translate the feature points by using the Euclidean matrix, and render the new points on the image plane. The key algorithm of this tracker is to estimate the Euclidean matrix by using a least square technique based on Lie algebra. The resulting tracker performed very well on the task of tracking a human face.

Natural versus artificial scene classification by ordering discrete fourier power spectra

Holistic representations of natural scenes is an effective and powerful source of information for semantic classification and analysis of arbitrary images. Recently, the frequency domain has been successfully exploited to holistically encode the content of natural scenes in order to obtain a robust representation for scene classification. In this paper, we present a new approach to naturalness classification of scenes using frequency domain. The proposed method is based on the ordering of the Discrete Fourier Power Spectra. Features extracted from this ordering are shown sufficient to build a robust holistic representation for Natural vs. Artificial scene classification. Experiments show that the proposed frequency domain method matches the accuracy of other state-of-the-art solutions. © 2008 Springer Berlin Heidelberg.

Cross-Lingual spoken language understanding from unaligned data using discriminative classification models and machine translation

This paper investigates several approaches to bootstrapping a new spoken language understanding (SLU) component in a target language given a large dataset of semantically-annotated utterances in some other source language. The aim is to reduce the cost associated with porting a spoken dialogue system from one language to another by minimising the amount of data required in the target language. Since word-level semantic annotations are costly, Semantic Tuple Classifiers (STCs) are used in conjunction with statistical machine translation models both of which are trained from unaligned data to further reduce development time. The paper presents experiments in which a French SLU component in the tourist information domain is bootstrapped from English data. Results show that training STCs on automatically translated data produced the best performance for predicting the utterance's dialogue act type, however individual slot/value pairs are best predicted by training STCs on the source language and using them to decode translated utterances. © 2010 ISCA.

Continuous F0 in the source-excitation generation for HMM-based TTS: Do we need voiced/unvoiced classification?

Most HMM-based TTS systems use a hard voiced/unvoiced classification to produce a discontinuous F0 signal which is used for the generation of the source-excitation. When a mixed source excitation is used, this decision can be based on two different sources of information: the state-specific MSD-prior of the F0 models, and/or the frame-specific features generated by the aperiodicity model. This paper examines the meaning of these variables in the synthesis process, their interaction, and how they affect the perceived quality of the generated speech The results of several perceptual experiments show that when using mixed excitation, subjects consistently prefer samples with very few or no false unvoiced errors, whereas a reduction in the rate of false voiced errors does not produce any perceptual improvement. This suggests that rather than using any form of hard voiced/unvoiced classification, e.g., the MSD-prior, it is better for synthesis to use a continuous F0 signal and rely on the frame-level soft voiced/unvoiced decision of the aperiodicity model. © 2011 IEEE.

A programme to carry out analysis of variance: two-way classification on Micro 2200

A brief description is given of a program to carry out analysis of variance two-way classification on MICRO 2200, for use in fishery data processing.

Comparative feature on design, construction and installation of three different model of low cost solar tunnel dryers

The study was conducted in collaboration with the ECFC project of the FAO (BGD/97/017) in Cox's Bazar to develop a low cost solar tunnel dryer for the production of high quality marine dried fish. The study areas were Kutubdiapara, Maheshkhali and Shahparirdip under Cox's Bazar district. Three different models of low cost solar dryer were constructed with locally available materials such as bamboo, wood, bamboo mat, hemp, canvas, wire, nails, rope, tin, polythene and net. Size of the dryers were: 20x4x3 ft ; 30x3x3 ft and 65x3x3 ft with the costs of Tk. 3060, 3530, 9600 for dryer 1, 2 and 3, respectively having different models. The drying capacities were 50, 150, 500 kg for dryer 1, 2 and 3 respectively. The average temperature range inside the dryers were 29-43°C, 34-51°C and 37-57°C for dryer 1, 2 and 3 respectively as recorded at 8:30h to 16:30h. The relative humidity were in the ranges of 22-42%, 27-39% and 24-41 % in dryer 1, 2 and 3 respectively. The fish samples used were Bombay duck, Silver Jew fish and Ribbon fish. The total drying time was in the range of 30-42, 28-38 and 24-34 hours to reach the moisture content of 12.3-14.5, 11.8-14.3, and 11.6-14.1% in dryer 1, 2 and 3 respectively. Among these three fish samples the drying was faster in Silver Jew fish followed by Bombay duck and Ribbon fish in all the three dryer.