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Learning Based Classifiers
| Content Provider | Scilit |
|---|---|
| Author | Kumar, Anil Upadhyay, Priyadarshi |
| Copyright Year | 2020 |
| Description | In this chapter, applications of learning based classifiers have been covered. Learning based classifiers use weights in their models. Learning based algorithms starting from artificial neural network (ANN), convolutional neural network (CNN), recurrent neural network (RNN), the hybrid learning based network model concept, and deep learning in remote sensing data processing have been included. Network structures, network parameters, and learning parameters with various layer combinations have been included. Also, a well-known problem in learning algorithms is a requirement of large training data sets. In the remote sensing domain, generating or collecting large training data is not possible. This issue has also been mentioned in this chapter. Book Name: Fuzzy Machine Learning Algorithms for Remote Sensing Image Classification |
| Related Links | https://content.taylorfrancis.com/books/download?dac=C2019-0-04871-4&isbn=9780429340369&doi=10.1201/9780429340369-4&format=pdf |
| Ending Page | 56 |
| Page Count | 24 |
| Starting Page | 33 |
| DOI | 10.1201/9780429340369-4 |
| Language | English |
| Publisher | Informa UK Limited |
| Publisher Date | 2020-07-09 |
| Access Restriction | Open |
| Subject Keyword | Book Name: Fuzzy Machine Learning Algorithms for Remote Sensing Image Classification Artificial Intelligence Artificial Neural Network Learning Based Based Classifiers |
| Content Type | Text |
| Resource Type | Chapter |
