A New Semi-supervised Classification Method of Hyperspectral Image based on Combining Renyi Entropy and Multinomial Logistic Regression Algorithm
نویسندگان
چکیده
منابع مشابه
Hyperspectral Image Classification Based on a Fast Bregman Sparse Multinomial Logistic Regression Algorithm
The Sparse Multinomial Logistic Regression (SMLR) method introduced in (Krishnapuram, 2005) is among the state-of-the-art in supervised learning. However its application to large datasets, such as hyperspectral imagery is still a rather challenging task from the computational point of view, sometimes even impossible to perform. In this paper, the Bregman iteration-based SMLR method (Bregman-SML...
متن کاملHyperspectral Image Classification Based on Semi-Supervised Rotation Forest
Ensemble learning is widely used to combine varieties of weak learners in order to generate a relatively stronger learner by reducing either the bias or the variance of the individual learners. Rotation forest (RoF), combining feature extraction and classifier ensembles, has been successfully applied to hyperspectral (HS) image classification by promoting the diversity of base classifiers since...
متن کاملExtreme Sparse Multinomial Logistic Regression: A Fast and Robust Framework for Hyperspectral Image Classification
A Fast and Robust Framework for Hyperspectral Image Classification Faxian Cao1, Zhijing Yang1*, Jinchang Ren2, Wing-Kuen Ling1 1 School of Information Engineering, Guangdong University of Technology, Guangzhou, 510006, China; [email protected]; [email protected]; [email protected] 2 Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow, G1 1XW, UK; jinchan...
متن کاملSemi Supervised Logistic Regression
Semi-supervised learning has recently emerged as a new paradigm in the machine learning community. It aims at exploiting simultaneously labeled and unlabeled data for classification. We introduce here a new semi-supervised algorithm. Its originality is that it relies on a discriminative approach to semisupervised learning rather than a generative approach, as it is usually the case. We present ...
متن کاملSemi-Supervised Based Hyperspectral Imagery Classification
Hyperspectral imagery classification is a challenging problem. Wherein, the high number of spectral channels and the high cost of true sample labeling greatly reduce the classification precision. In this paper, we proposed a semi-supervised method, which combine linear discriminant analysis and manifold learning, to improve the precision of hyperspectral imagery classification. Experimental res...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Signal Processing, Image Processing and Pattern Recognition
سال: 2014
ISSN: 2005-4254
DOI: 10.14257/ijsip.2014.7.5.06