Minima-YOLO: A Lightweight Identification Method for Lithium Mineral Components Under a Microscope Based on YOLOv8
Mineral identification technology is a critical technology in the construction of smart mines. To enable effective deployment and implementation of rapid mineral sorting for valuable ores on edge computing devices, we propose a lightweight identification method for lithium minerals under visible lig...
Saved in:
| Main Authors: | Zeyang Qiu, Xueyu Huang, Xiangyu Xu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-03-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/25/7/2048 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
PS-YOLO-seg: A Lightweight Instance Segmentation Method for Lithium Mineral Microscopic Images Based on Improved YOLOv12-seg
by: Zeyang Qiu, et al.
Published: (2025-07-01) -
YOLOv8n-SMMP: A Lightweight YOLO Forest Fire Detection Model
by: Nianzu Zhou, et al.
Published: (2025-05-01) -
YOLOv8-EMSC: A lightweight fire recognition algorithm for large spaces
by: Deng Li, et al.
Published: (2024-12-01) -
GPC-YOLO: An Improved Lightweight YOLOv8n Network for the Detection of Tomato Maturity in Unstructured Natural Environments
by: Yaolin Dong, et al.
Published: (2025-02-01) -
PCPE-YOLO with a lightweight dynamically reconfigurable backbone for small object detection
by: Weijia Chen, et al.
Published: (2025-08-01)