美国密西西比州立大学Jenny Q. Du教授学术报告

来源:信息科学与技术学院  作者:李恒超  日期:2017-06-04  点击数:742

西南交通大学
信息科学与技术学院学术讲座

讲座时间:20170605日(星期一) 上午10:00

讲座地点:犀浦校区九教9428#

主  讲  人:Prof. Jenny Q. Du

                 Department of Electrical and Computer Engineering

                 Mississippi State University

主  持  人:信息科学与技术学院  李恒超教授

讲座题目(Title)Extreme Learning Machine for Efficient Hyperspectral Image Classification

内容简介(Abstract)

Extreme learning machine (ELM) is a feedforward neural network with one hidden layer, which is similar to a multilayer perceptron (MLP). To reduce the complexity in the training process of MLP using the traditional backpropagation algorithm, the weights in an ELM between input and hidden layers are random variables. The output layer is linear, as in a radial basis function neural network (RBFNN), so the output weights can be easily estimated with a least squares solution. The computational cost of the ELM is much lower than the standard support vector machine (SVM), and a kernel version of the ELM (i.e., KELM) can offer comparable performance as the SVM. In our previous work, we investigate the impact of the number of hidden neurons to the performance of both ELM and KELM. Basically, more hidden neurons are needed if the number of training samples and data dimensionality are large, which results in a very large matrix inversion problem. To avoid handling such a large matrix, we propose to conduct band selection to reduce data dimensionality (i.e., the number of input neurons), thereby reducing network complexity. Experimental results on hyperspectral remote sensing images show that ELM and KELM using selected bands can yield similar or even better classification accuracy than the counterparts using all the original bands.

主讲人简介(Biography)

Dr. Du is Bobby Shackouls Professor with the Department of Electrical and Computer Engineering, Mississippi State University, USA. Her research interests include hyperspectral remote sensing image analysis and applications, pattern recognition, and machine learning. Dr. Du is a Fellow of SPIE-International Society for Optics and Photonics. She served as Co-Chair for the Data Fusion Technical Committee of IEEE Geoscience and Remote Sensing Society (GRSS) in 2009–2013, and Chair for Remote Sensing and Mapping Technical Committee of International Association for Pattern Recognition (IAPR) in 2010–2014. She served as Associate Editor for IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2011–2015), IEEE Signal Processing Letters (2012–2015), and Journal of Applied Remote Sensing (2014–2015). Currently, Dr. Du is the Editor-in-Chief of IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS). She was the Guest Editor of several special issues published in IEEE Transactions on Geoscience and Remote Sensing, IEEE JSTARS, Journal of Applied Remote Sensing, Pattern Recognition Letters, and Remote Sensing.


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主办:研究生院
承办:信息科学与技术学院