Prof Radhakanta Koner presented the work on low-cost 3D fragmentation measurement techniques based on an unsupervised machine learning approach at the World Mining Congress 2023 in the Artificial Intelligence session at Brisbane, Australia

1 July, Dhanbad: 

Prof Radhakanta Koner, Prof-In-Charge of Rock Slope Engineering Lab, Department of Mining Engineering, Indian Institute of Technology (Indian School of Mines) Dhanbad, presented the paper “A 3D Rock Fragmentation Measurement Technique: Combining The Structure From Motion Technique and Unsupervised Machine Learning” at the 26th World Mining Congress 2023 held at Brisbane Australia from 26 June to 29 June 2023. 

The paper's first author was Mr Adabala Sai Naresh, Senior Research Fellow, Department of Mining Engineering. The work is supported by Science Engineering Research Board, New Delhi Core-Research Grant (CRG/2020/005919).

The salient point of the work is that it has broadly used unsupervised methods of machine learning techniques, so preliminary data and training data requirement is nil, which gives rise to the broad applicability of the processes in allied domain particle size distribution analysis in touch-free ways.

The added advantage of the method is the use of the Convex-hull minimum bounding box algorithm, which is computationally very inexpensive, so all range of users with low processing power computational facility can also use it for the size estimation of the block concerned.

The methods show broad applicability from mines to mills in the Mining Engineering process.

Rock Slope Engineering lab acknowledges the help and supports the Department of Mining Engineering extended to carry out the work. 

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