Online particle size analysis on conveyor belts with dense convolutional neural networks

Author:

Fu Yihao,Aldrich ChrisORCID

Funder

Minerals Research Institute of Western Australia

Publisher

Elsevier BV

Subject

Mechanical Engineering,Geotechnical Engineering and Engineering Geology,General Chemistry,Control and Systems Engineering

Reference60 articles.

1. SLIC superpixels compared to state-of-the-art superpixel methods;Achanta;IEEE Trans. Pattern Anal. Mach. Intell.,2012

2. Aldrich, C., Jemwa. G.T., Rama, M., 2009. Online analysis of coal fines on a conveyor belt by use of machine vision and kernel methods. South African Chemical Engineering Congress, Cape Town, Western Cape, South Africa, 20-22 September, published on CD-ROM, ISBN: 978-1-920355-21-0.

3. Online analysis of coal on a conveyor belt by use of machine vision and kernel methods;Aldrich;Int. J. Coal Prep. Util.,2010

4. Estimation of the size distribution of particles moving on a conveyor belt;Al-Thyabat;Miner. Eng.,2007

5. Estimation of particulate fines on conveyor belts by use of wavelets and morphological image processing;Amankwah;Int. J. Mach. Learn. Comput.,2011

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