Identification of Tomato Disease Types and Detection of Infected Areas Based on Deep Convolutional Neural Networks and Object Detection Techniques
Table 2
The specific information of the dataset.
Diseases
Original1
Expanded2
Training3
Validation4
Test5
Healthy tomato
64
320
150
105
65
Tomato malformed fruit
38
190
90
60
40
Tomato blotchy ripening
16
80
35
25
20
Tomato puffy fruit
22
110
50
35
25
Tomato dehiscent fruit
35
175
80
60
35
Tomato blossom-end rot
18
90
40
30
20
Tomato sunscald
14
70
30
25
15
Tomato virus disease
34
170
80
55
35
Tomato gray mold
28
140
65
45
30
Tomato ulcer disease
9
45
20
15
10
Tomato anthracnose
8
40
15
15
10
Total
286
1430
655
470
305
1Number of original images; 2number of processed images; 3number of images in the training set; 4number of images in the validation set; 5number of images in the test set.