COMPARISON OF VARIOUS CLASSIFICATION ALGORITHMS FOR POLARIMETRIC SAR IMAGE CLASSIFICATION
Published In: INTERNATIONAL CONFERENCE ON ADVANCED COMPUTING, COMMUNICATION AND NETWORKS
Author(s): NITIN SHARMA , PURNIMA AHUJA
Abstract: In this paper, variety of classifiers for supervised target classification of polarimetric synthetic aperture radar (SAR) image explained. Compared to traditional classifiers such as ML classification,complex Wishart distribution or Adabo0st classifier, the SVM (Support Vector Machine) method is more robust, accurate and flexible. This algorithm not only uses a statistical classifier, but also preserves the purity of dominant polarimetric scattering properties. Different features or parameters e
- Publication Date: 03-Jun-2011
- DOI: 10.15224/978-981-07-1847-3-1027
- Views: 0
- Downloads: 0
SECURE COMPRESSION OF BITMAP CHARACTER USING ARTIFICIAL NEURAL NETWORK FOR TRANSMISSION
Published In: INTERNATIONAL CONFERENCE ON ADVANCED COMPUTING, COMMUNICATION AND NETWORKS
Author(s): ANJALI SINGH , DEEPIKA GUPTA , MOHIT ARORA , PRIYANKA GAUR
Abstract: The transmission of data across communication paths is an expensive process in respect time and bandwidth. Data compression is usually obtained by substituting a shorter symbol for an original symbol in the source data, which should contain the same information but with a smaller representation in length. The purpose of this paper is to show that neural networks may be promising tools for data compression without loss of information. We combine neural nets, standard statistical compression metho
- Publication Date: 03-Jun-2011
- DOI: 10.15224/978-981-07-1847-3-1027
- Views: 0
- Downloads: 0