Imaging Software Gains Enhanced Support For Classification Using Deep Learning

Other new functionality includes a revamped plus augmented 3D display, processing, and analysis offer. The service pack expands the capabilities of its classification tools, which make use of deep learning technology—specifically convolutional neural networks (CNNs)—to analyze images of highly textured, naturally varying, and acceptably deformed goods. To perform inference, the CNN must first undergo training. MIL X provides the necessary infrastructure to build the required training dataset—including the labeling of images and augmenting the dataset with synthesized images—as well as monitoring and analyzing the training process. It supports different types of training, such as transfer learning and fine-tuning, all starting from one of the supplied pre-defined CNN architectures. Users can opt to train a CNN on their own, or they can continue to engage the company’s team of vision experts to perform the training on the users’ behalf. The service pack’s image-oriented classification makes use of deep learning technology in two distinct approaches: a global approach that assigns images to classes and a coarse segmentation approach that maps image neighborhoods according to categories. The latter ultimately identifies and roughly locates the presence of specific features or defects. Other features of the service pack include HDR imaging within registration toolset and faster prototyping and development with MIL CoPilot.

>>For more information on this product, click here
Matrox Imaging
www.matrox.com
514.822.6000