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https://www.ai.rug.nl/~mwiering/GROUP/ARTICLES/ensemble-deep-svm.pdf
Keywords-Image categorization, support vector machines, ensemble methods, product rule, deep architectures I. INTRODUCTION MACHINE VISION is a subfield of artificial intelli-gence that focuses on extracting useful information from images. During the last decade a large number of novel algorithms have been described for image recogni-
https://www.researchgate.net/publication/228340984_An_Ensemble_of_Deep_Support_Vector_Machines_for_Image_Categorization
This paper presents the deep support vector ma-chine (D-SVM) inspired by the increasing popularity of deep belief networks for image recognition. Our deep SVM trains an SVM in the standard way and ...
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.592.7094
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Abstract—This paper presents the deep support vector ma-chine (D-SVM) inspired by the increasing popularity of deep belief networks for image recognition. Our deep SVM trains an SVM in the standard way and then uses the kernel activations of support vectors as inputs for training another SVM at the next layer.
https://www.academia.edu/2739798/An_ensemble_of_deep_support_vector_machines_for_image_categorization
Abstract This paper presents the deep support vector machine (D-SVM) inspired by the increasing popularity of deep belief networks for image recognition. Our deep SVM trains an SVM in the standard way and then uses the kernel activations of support
https://ieeexplore.ieee.org/document/5370984/
An Ensemble of Deep Support Vector Machines for Image Categorization Abstract: This paper presents the deep support vector machine (D-SVM) inspired by the increasing popularity of deep belief networks for image recognition. Our deep SVM trains an SVM in the standard way and then uses the kernel activations of support vectors as inputs for ...
https://www.sciencedirect.com/science/article/pii/S0950705116301605
1. Introduction. For the classification problem, the performance of learning algorithms extremely depends on the nature of data representation .In 2006, Geoff Hinton reported a significant breakthrough in the feature extraction, and firstly proposed the concept of “Deep Learning (DL)” , .After then, DL has generated considerable recent research interest in various fields , , , .Cited by: 19
http://yadda.icm.edu.pl/yadda/element/bwmeta1.element.ieee-000005370984
An Ensemble of Deep Support Vector Machines for Image Categorization ... image recognition machine vision deep support vector machines image categorization deep belief networks image recognition kernel activations Caltech object database Corel dataset ... 2009 International Conference of Soft Computing and Pattern Recognition ...
https://core.ac.uk/display/102023766
Abstract—This paper presents the deep support vector ma-chine (D-SVM) inspired by the increasing popularity of deep belief networks for image recognition. Our deep SVM trains an SVM in the standard way and then uses the kernel activations of support vectors …
https://www.deepdyve.com/lp/elsevier/when-ensemble-learning-meets-deep-learning-a-new-deep-support-vector-yvX0UYnvqC
Sep 01, 2016 · Read "When Ensemble Learning Meets Deep Learning: a New Deep Support Vector Machine for Classification, Knowledge-Based Systems" on DeepDyve, the largest online rental service for scholarly research with thousands of academic publications available at your fingertips.
https://www.narcis.nl/publication/RecordID/oai%3Apure.rug.nl%3Apublications%2Fb720f8ab-ab4c-4627-95cb-566c757c43e0
This paper presents the deep support vector machine (D-SVM) inspired by the increasing popularity of deep belief networks for image recognition. Our deep SVM trains an SVM in the standard way and then uses the kernel activations of support vectors as inputs for training another SVM at the next layer.Cited by: 24
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