Search alternatives:
segmentation algorithm » selection algorithm (Expand Search)
derived optimization » driven optimization (Expand Search), required optimization (Expand Search), design optimization (Expand Search)
texture segmentation » tumor segmentation (Expand Search), net segmentation (Expand Search), text augmentation (Expand Search)
image texture » image features (Expand Search), image capture (Expand Search)
task derived » risks derived (Expand Search), ipsc derived (Expand Search), data derived (Expand Search)
binary task » binary mask (Expand Search)
segmentation algorithm » selection algorithm (Expand Search)
derived optimization » driven optimization (Expand Search), required optimization (Expand Search), design optimization (Expand Search)
texture segmentation » tumor segmentation (Expand Search), net segmentation (Expand Search), text augmentation (Expand Search)
image texture » image features (Expand Search), image capture (Expand Search)
task derived » risks derived (Expand Search), ipsc derived (Expand Search), data derived (Expand Search)
binary task » binary mask (Expand Search)
-
1
-
2
-
3
Table_1_Fusion of fruit image processing and deep learning: a study on identification of citrus ripeness based on R-LBP algorithm and YOLO-CIT model.docx
Published 2024“…Instead of traditional convolution, Ghostconv is utilized by the neck network of the YOLO-CIT model. The fruit segment of citrus in the original citrus images processed by the R-LBP algorithm is combined with the background segment of the citrus images after grayscale processing to construct synthetic images, which are subsequently added to the training dataset. …”
-
4
-
5
-
6
-
7
-
8
-
9
-
10
-
11
-
12
-
13
-
14
-
15
-
16
-
17
-
18
-
19
-
20