Convolutional Neural Networks Optimized by Logistic Regression Model - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2016

Convolutional Neural Networks Optimized by Logistic Regression Model

Abstract

In recent years, convolutional neural networks have been widely used, especially in the field of large scale image processing. This paper mainly introduces the application of two kinds of logistic regression classifier in the convolutional neural network. The first classifier is a logistic regression classifier, which is a classifier for two classification problems, but it can also be used for multi-classification problems. The second kind of classifier is a multi-classification logistic regression classifier, also known as softmax regression classifier. Two kinds of classifiers have achieved good results in MNIST handwritten digit recognition.
Fichier principal
Vignette du fichier
433802_1_En_10_Chapter.pdf (341.07 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01614983 , version 1 (11-10-2017)

Licence

Attribution

Identifiers

Cite

Bo Yang, Zuopeng Zhao, Xinzheng Xu. Convolutional Neural Networks Optimized by Logistic Regression Model. 9th International Conference on Intelligent Information Processing (IIP), Nov 2016, Melbourne, VIC, Australia. pp.91-96, ⟨10.1007/978-3-319-48390-0_10⟩. ⟨hal-01614983⟩
177 View
301 Download

Altmetric

Share

Gmail Facebook X LinkedIn More