EVS-SC200 Deep Learning Smart Camera
Easy access. Effectively solve simple to complex issues such as OCR, assembly verification, counting, defect detection, classification, etc. Empowering production and assembly process control and benefitting businesses on high-yield production rates. Improving automotive, pharmaceuticals/medical, and food packaging industries' intelligent upgrading by our fast formed industrial solution which has no intricate parameter tuning and software integration required.
No visual algorithm skills or AI background requirements. No fine-tuning needs on parameter and imaging. Algorithm highly generalized, able to autonomously achieves high-quality detection.
Launch in 1 Day
Code-free, guided operation, mastered upon unboxing. Algorithm supports Few samples/Positive samples/Preset models, with deployment cycles completed in 1 day.
More than “Simple Application”
Leveraging the accumulated industrial AI algorithm capabilities of Aqrose. Fine or low contrast defects are detectable. Poor consistency, substantial interference, and fuzzy defects are detectable.
Ultra-fast image analysis
Targeted, optimized AI algorithms, capable of processing thousands of products per minute, meets requirements of majority production lines.
Embedded with a deep learning pre-trained font library, we eliminate the need for annotated training and break conventional algorithmic techniques' limitations.
Recognition of characters with interference
Recognition of characters on different materials
Recognition of characters in irregular shapes
Abnormal angles of assembly components
Abnormal component types and sizes
Presence or absence of components within a specific region, etc.
Customize the template, learn the shape, color, and other characteristics of the components/parts, and check whether the assembly is correct through comparison.
Objects to be inspected are classified based on common characteristics for categorization. This may involve binary classification into OK/NG based on color, type, grade, and other criteria.
To detect moderate and minor defects precisely, this AI-powered solution learns the differences from images of defect-free products and rejects them to identify the defect regions.
By leveraging advanced learning techniques, the solution can accurately identify and count target components with varying orientations by analyzing their shape, texture, and other distinctive features.