Radial basis functions for multivariable interpolation: a review
Algorithms for approximation
Decision estimation and classification: an introduction to pattern recognition and related topics
Decision estimation and classification: an introduction to pattern recognition and related topics
Multilayer feedforward networks are universal approximators
Neural Networks
Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
The nature of statistical learning theory
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Pattern classification: a unified view of statistical and neural approaches
Pattern classification: a unified view of statistical and neural approaches
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
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Three learning phases for radial-basis-function networks
Neural Networks
Multi-Classification by Using Tri-Class SVM
Neural Processing Letters
Computer Processing of Remotely-Sensed Images: An Introduction
Computer Processing of Remotely-Sensed Images: An Introduction
Fast learning in networks of locally-tuned processing units
Neural Computation
SPPRA '08 Proceedings of the Fifth IASTED International Conference on Signal Processing, Pattern Recognition and Applications
Fuzzy-input fuzzy-output one-against-all support vector machines
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part III
Comparison of multiclass SVM decomposition schemes for visual object recognition
PR'05 Proceedings of the 27th DAGM conference on Pattern Recognition
Using dempster-shafer theory in MCF systems to reject samples
MCS'05 Proceedings of the 6th international conference on Multiple Classifier Systems
IEEE Transactions on Image Processing
Support Vector Machines and MLP for automatic classification of seismic signals at Stromboli volcano
Proceedings of the 2009 conference on Neural Nets WIRN09: Proceedings of the 19th Italian Workshop on Neural Nets, Vietri sul Mare, Salerno, Italy, May 28--30 2009
Computer Speech and Language
Pattern classification and clustering: A review of partially supervised learning approaches
Pattern Recognition Letters
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We compared the performance of several supervised classification algorithms on multi-source remotely sensed images. Apart from the Multi-Layer Perceptron, K-Nearest-Neighbour and Radial Basis Function network approaches, we looked more in detail at the Support Vector Machine classifier, which recently showed promising results in our setting. In particular, it is able to provide meaningful answers for the analysis of mixed pixels. They correspond to areas on the ground that comprise more than one distinct class, representing a major challenge for the interpretability of the final land-cover maps. To assess their impact, we performed a rejection-based analysis, allowing classifiers to refuse answers on pixels they can not associate mainly with one class. The experimental results lead to the conclusion that 1vs1 SVM approach with a linear kernel (using Bradley-Terry coupling) has to be preferred over all other classification algorithms examined, both in terms of accuracy as well as ease of visual interpretation.