| 427 - 427 |
Selected papers from Automated Mineralogy'06, Brisbane, Australia, July 2006 - Foreword
Pownceby M |
| 428 - 434 |
Semi-automated petrographic assessment of coal by coal grain analysis
O'Brien G, Jenkins B, Ofori P, Ferguson K |
| 435 - 443 |
Mineralogical imaging of kimberlites using SEM-based techniques
Benvie B |
| 444 - 451 |
Mineral characterisation by EPMA mapping
Pownceby MI, MacRae CM, Wilson NC |
| 452 - 460 |
Estimation of mineral grain size using automated mineralogy
Sutherland D |
| 461 - 471 |
Utilization of optical image analysis and automatic texture classification for iron ore particle characterisation
Donskoi E, Suthers SP, Fradd SB, Young JM, Campbell JJ, Raynlyn TD, Clout JMF |
| 472 - 479 |
Towards a virtual metallurgical plant 2: Application of mineralogical data
Adams MD |
| 480 - 486 |
The campaign survey model - A case study at Raglan mine, Quebec
Lotter NO, Laplante AR |
| 487 - 495 |
QEMSCAN analysis as a tool for improved understanding of gravity separator performance
Pascoe RD, Power MR, Simpson B |
| 496 - 505 |
Automated mineralogical analysis of coal and ash products - Challenges and requirements
van Alphen C |
| 506 - 517 |
An overview of the advantages and disadvantages of the determination of gold mineralogy by automated mineralogy
Goodall WR, Scales PJ |
