[AI Image Inspection Case] Strawberry Harvesting Season
We will determine the harvest time of strawberries using AI image inspection software!
At the request of a manufacturer of industrial equipment, we conducted a simple evaluation to determine the harvest timing of strawberries. We used 58 sample images for the inspection. (34 strawberries were classified as OK and 24 as NG) 【Inspection Settings and Results】 As a result, all "harvestable strawberries" were correctly detected. Teacher Images: Correct Judgment 100% (20/20) Incorrect Judgment 0% (0/20) Unlearned Images: 94% (32/38) 6% (2/38) Total: 96% (56/58) 4% (2/58) However, among the strawberries classified as NG, two strawberries that appeared close to OK when viewed by the human eye were mistakenly classified as harvestable. (1) Still pinkish in color, therefore not harvestable... NG1 (Pink) (2) Still white or green, therefore not harvestable... NG2 (White or Green) (3) Strawberries that can be harvested... Harvest OK By creating three types of labels and training the software, it will adjust its own setting parameters and improve recognition. The images are annotated.
basic information
Annotation refers to the task of enclosing the parts you want to detect with rectangles. The annotated images become "training images" for the software to learn from. This time, we performed annotation work on 10 images. [Software Used] Software: DeepSky
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