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Scientific Programming
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2020
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Article
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Tab 5
Research Article
Detecting Citrus in Orchard Environment by Using Improved YOLOv4
Table 5
Identification parameters of four methods for different occlusion degrees.
Occlusion condition
Model
Citrus count
Correctly identified
Falsely identified
Missed
Amount
Rate (%)
Amount
Rate (%)
Amount
Rate (%)
Less than 50%
Faster-RCNN
200
162
81.24
19
9.71
31
15.44
YOLOv3
200
156
78.22
23
11.52
38
18.96
YOLOv4
200
173
86.38
14
7.10
22
11.21
Improved YOLOv4
200
187
93.58
12
5.98
16
8.15
More than 50%
Faster-RCNN
200
156
78.24
26
12.81
39
19.34
YOLOv3
200
148
74.22
35
17.52
46
22.96
YOLOv4
200
166
83.18
20
10.05
26
13.07
Improved YOLOv4
200
182
90.82
14
7.18
21
10.36