| 1 |
Multi-information online detection of coal quality based on machine vision
Zhang ZL, Liu Y, Hu Q, Zhang ZW, Wang L, Liu X, Xia XH
Powder Technology, 374, 250, 2020 |
| 2 |
Bilateral telerobotic system using Type-2 fuzzy neural network based moving horizon estimation force observer for enhancement of environmental force compliance and human perception
Sun D, Liao QF, Stoyanov T, Kiselev A, Loutfi A
Automatica, 106, 358, 2019 |
| 3 |
An intelligent machine vision-based smartphone app for beef quality evaluation
Hosseinpour S, Ilkhchi AH, Aghbashlo M
Journal of Food Engineering, 248, 9, 2019 |
| 4 |
Machine learning applications in minerals processing: A review
McCoy JT, Auret L
Minerals Engineering, 132, 95, 2019 |
| 5 |
Machine vision based monitoring and analysis of a coal column flotation circuit
Massinaei M, Jahedsaravani A, Taheri E, Khalilpour J
Powder Technology, 343, 330, 2019 |
| 6 |
Systematic study of sol-gel parameters on TiO2 coating for CO2 photoreduction
Thompson WA, Perier C, Maroto-Valer MM
Applied Catalysis B: Environmental, 238, 136, 2018 |
| 7 |
Rapid prediction of single green coffee bean moisture and lipid content by hyperspectral imaging
Caporaso N, Whitworth MB, Grebby S, Fisk ID
Journal of Food Engineering, 227, 18, 2018 |
| 8 |
Froth image analysis by use of transfer learning and convolutional neural networks
Fu YH, Aldrich C
Minerals Engineering, 115, 68, 2018 |
| 9 |
Automatic characterisation of chars from the combustion of pulverised coals using machine vision
Chaves D, Fernandez-Robles L, Bernal J, Alegre E, Trujillo M
Powder Technology, 338, 110, 2018 |
| 10 |
Development of a machine vision system for real-time monitoring and control of batch flotation process
Jahedsaravani A, Massinaei M, Marhaban MH
International Journal of Mineral Processing, 167, 16, 2017 |
