Intelligent Deployment Solution for Tabling Adapting Deep Learning

Abstract

This article presents an intelligent deployment solution for tabling that utilizes deep learning techniques. The solution involves adapting deep learning semantic segmentation algorithms with DeepLab V3+ to extract multi-dimensional image features, enabling the mapping of relationships between mineral ore belt characteristics and operating parameters using a multi-output support vector regression model optimized using a sparrow search algorithm (ssa-msvr). The proposed solution integrates image recognition software and data processing method, which significantly improves the efficiency and effectiveness of mineral processing, providing a promising avenue for further research and development in this field.

Keywords

• Mineral processing
• deep learning semantic segmentation
• multi-dimensional image features
• support vector regression model