Knowledge of Visual Inspection: Verification in Deep Learning (Object Recognition)
I will explain how to proceed with validation in AI (deep learning).
One common question from companies considering the introduction of image recognition and inspection using deep learning is, "How many images do we need to prepare for inspection?" The conclusion is that it cannot be definitively stated. This is because the amount of data required varies significantly depending on the complexity of the object's appearance (color, shape, angle, etc.) and the changing features. In this article, we have organized the basic verification process as follows: 1. Capture images of the product to be inspected and collect approximately a few hundred images (for example, around 200). 2. Select half of those images and provide "annotations" for the object. 3. Use the annotated data as training data for the AI and validate it with the remaining images (testing for recognition). 4. If there are misrecognitions or missed recognitions, increase the number of images or review the annotations and retry. 5. Repeat this "data augmentation → training → validation → readjustment" process until satisfactory accuracy is achieved. *For more details, please refer to the related link (blog).
basic information
*For more details, please see the related link (blog).
Price range
Delivery Time
Applications/Examples of results
For more details, please see the related link (blog).
catalog（1）
Download All Catalogs
Recommended products
Distributors
"Achieve significant effects" while "keeping costs down." It requires endless effort despite its simplicity. This is why SkyLogic believes it is valuable to continue pursuing "cost-effectiveness" through means such as technology and services. EasyInspector2/DeepSky: An appearance inspection software with a cumulative installation record of 2,500. Effect: We have developed a high-precision and lightweight AI model. It can connect five cameras simultaneously to one PC. Cost: To reduce the cost of learning setup, it is no-code, and simply deciding the inspection mode determines the necessary processing. Expansion and horizontal deployment are possible at low cost. EasyMonitoring2: A system that accurately reads and records meters through cameras and notifies of abnormalities, eliminating time-consuming and costly patrol monitoring. Effect: Not only meter reading but also the confirmation of processing tanks and oil leaks can be automated using AI. Cost: It can connect to inexpensive cameras, up to 100, with one PC. There are no monthly fees. In addition to these, we offer various products for "cost-effectiveness." Please let us know your company's challenges and themes.