AI Appearance Inspection [RoxyAI] Function Upgrade

basic information

**Features Added in the Version Upgrade** 1. Hint Function If the AI does not capture the characteristics of defects, accuracy will not improve. The hint function added in V1.14 makes it easier to learn the characteristics of defects by masking areas other than the defective parts. 2. Enhanced Image Augmentation Additional augmentation methods have been added to enrich the types of augmented images. 3. Strengthened Learning Function A learning method has been added that is expected to improve generalization performance at the cost of learning speed. Learning time will be approximately 1.5 times longer (varies depending on learning settings). You can specify whether to use this function in the learning settings screen. 4. Expansion of Base Models for Type 3 Base models that can be used with Type 3 have been added. You can select base models according to your needs, such as speed-oriented or accuracy-oriented. 5. Addition of Sub-Windows Images filtered by purpose are displayed in a sub-window, reducing the effort required to search for images. 6. Batch Learning Result Comparison You can view and compare various metrics and settings from the results of batch executions. 7. Others Improvements in usability, speed enhancements, and bug fixes, etc.

Price information

The three machines are proposal-based and support our customers' "troubles." 【Purchase Method】 In addition to cash lump-sum purchases, we can propose payment plans that meet our customers' needs in collaboration with partner leasing companies. Recently, there are also leases that can ultimately be converted into company assets. Additionally, we can assist with various subsidies. If you have any concerns, please feel free to contact us.

Delivery Time

Applications/Examples of results

【Other Features】 - The AI automatically extracts suspicious data from the learning data. - Focused checks on intervals where normal and defective data are mixed on the histogram. - Human judgment on the handling of suspicious data by reviewing enlarged images and overall images. - If issues are found, the corresponding images are deleted or normal/defective classifications are swapped. 【Examples of Achievements】 - Scratches (line scratches, dents) on metal products, processing defects (surface inspection after welding and burr removal). - Scratches (line scratches, dents, sink marks) on resin molded products, processing defects (burrs, chips). - Sensory inspection for shape defects such as weld beads and soldering. *This does not guarantee the detection of all defects.