What question did this study set out to answer?

The aim is to develop an efficient, intelligent sorting system for coal and gangue using machine vision technology.

March 10, 2026

An Intelligent Sorting System of Coal-Gangue Based on Machine Vision and Convolutional Neural Network

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An intelligent system sorts coal and gangue using machine vision and deep learning, improving efficiency in mining operations.

The aim is to develop an efficient, intelligent sorting system for coal and gangue using machine vision technology.
Utilized OpenMV for image capturing of coal and gangue.
Employed MobileNetV2-based FOMO model for target detection training in the cloud.
Sent position data of gangue to STM32 microcontroller for processing and path planning.
Controlled a robotic arm and conveyor belt for sorting action.
Achieved an F1 score of 95.5% and a recall of 91.3% with the FOMO model.
Test accuracy of 97.56% for coal gangue identification.
Robotic arm sorting success rate reached 90.13% with a positioning error between 9 and 12.5 mm.

A 2026 study studied this question.

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