The Euresys EasyClassify requires the user to label training images, that is to tell which ones are good and which ones are bad, or which ones belong to which class. After this learning/training process, the Euresys EasyClassify library is able to classify images. For any given image, it returns a list of probabilities, showing the likelihood that the image belongs to each of the classes it has been taught. For example, if the process requires setting apart bad parts from good ones, EasyClassify returns whether each part is good or bad, and with what probability. Euresys EasyClassify is the classification tool of Deep Learning Bundle.
What is EasyClassify Good for?
Deep Learning is generally not suitable for applications requiring precise measurement or gauging. It is also not recommended when some types of errors (such as false negative) are completely unacceptable. Euresys EasyClassify performs better than traditional machine vision when the defects are difficult to specify explicitly, for example, when the classification depends on complex shapes and textures at various scales and positions.
What is Deep Learning?
Neural Networks are computing systems inspired by the biological neural networks that constitute the human brain. Convolutional Neural Networks (CNN) are a class of deep, feed-forward artificial neural networks, most commonly applied to analyzing images. Deep Learning uses large CNNs to solve complex problems difficult or impossible to solve with so-called conventional computer vision algorithms. Deep Learning algorithms may be easier to use as they typically learn by example. They do not require the user to figure out how to classify or inspect parts. Instead, in an initial training phase, they learn just by being shown many images of the parts to be inspected. After successful training, they can be used to classify parts or detect and segment defects.
- Includes functions for classifier training and image classification
- Able to detect defective products or sort products into various classes
- Supports data augmentation, works with as few as one hundred training images per class
- Compatible with CPU and GPU processing
- Includes the free Deep Learning Studio application for dataset creation, training, and evaluation
- Only available as part of the Deep Learning Bundle
- Mark inspection
- LED inspection
- Presence / Absence check
- Surface analysis
- Assembly inspection
- Code quality verification for label printing machines
- Food inspection and sorting