Semi-supervised learning with convolutional neural networks for UAV images automatic recognition

Author:

Amorim Willian Paraguassu,Tetila Everton Castelão,Pistori Hemerson,Papa João Paulo

Funder

CNPq

FAPESP

FUNDUNESP

FUNDECT

Publisher

Elsevier BV

Subject

Horticulture,Computer Science Applications,Agronomy and Crop Science,Forestry

Reference43 articles.

1. A multiple labeling-based optimum-path forest for video content classification;Pereira,2013

2. Improving semi-supervised learning through optimum connectivity;Amorim;Pattern Recogn.,2016

3. W.P. Amorim, A.X. Falcão, M.H. Carvalho, Semi-supervised pattern classification using optimum-path forest, in: 2014 27th SIBGRAPI Conference on Graphics, Patterns and Images, 2014, pp. 111–118.

4. N. Bridle, X. Zhu, p-voltages: Laplacian regularization for semi-supervised learning on high-dimensional data, Workshop on Mining and Learning with Graphs (MLG2013).

5. Regularized extreme learning machine for multi-view semi-supervised action recognition;Iosifidis;Neurocomputing,2014

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