Smart Agriculture ›› 2022, Vol. 4 ›› Issue (3): 120-131.doi: 10.12133/j.smartag.SA202207001
• Special Issue--Key Technologies and Equipment for Smart Orchard • Previous Articles Next Articles
SHANG Fengnan1,2,3(), ZHOU Xuecheng1,2,3(
), LIANG Yingkai1,2,3, XIAO Mingwei1,2,3, CHEN Qiao1,2,3, LUO Chendi1,2,3
Received:
2022-06-30
Online:
2022-09-30
Published:
2022-11-23
corresponding author:
ZHOU Xuecheng
E-mail:shangfengnan@163.com;zxcem@scau.edu.cn
CLC Number:
SHANG Fengnan, ZHOU Xuecheng, LIANG Yingkai, XIAO Mingwei, CHEN Qiao, LUO Chendi. Detection Method for Dragon Fruit in Natural Environment Based on Improved YOLOX[J]. Smart Agriculture, 2022, 4(3): 120-131.
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URL: http://www.smartag.net.cn/EN/10.12133/j.smartag.SA202207001
Table 4
Comparison of dragon fruit detection results of different networks
网络模型 | 模型大小/MB | 帧率/(f·s-1) | 平均时间/ms | F | AP0.5/% | AP0.5:0.95/% | APS/% | APM/% | APL/% |
---|---|---|---|---|---|---|---|---|---|
YOLOX-Nano+CBAM | 3.76 | 46 | 21.72 | 0.99 | 98.9 | 72.4 | 56.2 | 63.3 | 78.0 |
YOLOv5-S | 27.10 | 59 | 16.87 | 0.93 | 91.0 | 59.5 | 29.0 | 49.8 | 66.5 |
MobileNetV3-YOLOv4 | 53.70 | 44 | 22.66 | 0.94 | 91.8 | 55.4 | 38.8 | 44.8 | 62.6 |
YOLOv4-Tiny | 22.40 | 145 | 6.88 | 0.91 | 89.1 | 54.4 | 25.5 | 42.6 | 62.2 |
YOLOv3 | 235.00 | 51 | 19.38 | 0.83 | 72.7 | 41.4 | 1.7 | 31.0 | 49.7 |
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