# About This Release

As the release of VisionPro Deep Learning 1.1.0, VisionPro Deep Learning now provides Red Analyze High Detail mode (Supervised), which is a more powerful version of Red Analyze Supervised in terms of segmentation task accuracy. By this addition of a new mode in Red Analyze tool families, the previous Red Analyze Supervised/Unsupervised tools are re-categorized to Red Analyze Focused Supervised/Unsupervised. For more details, please refer to Red Analyze tool.

The one other important feature we adopted in 1.1.0 is Loss Inspector, a tool developed to assist you when training High Detail modes to create a better neural network model. You can monitor the change of Validation Loss and to do so you can evaluate how desirably the training is going on or bring a judgment call on the performance of a trained model based on its best validation loss.

[New Content]

- Red Analyze High Detail Mode

- A new solution with a powerful new architecture for supervised segmentation tasks that were previously only handled by Red Analyze Supervised Mode. With the addition of Red Analyze High Detail Mode, Red Analyze tools are now reorganized and fall into the following category:

  Name | Architecture | Mode
  --- | --- | ---
  Red Analyze High Detail | High Detail | Supervised
  Red Analyze Supervised | Focused | Supervised
  Red Analyze Unsupervised | Focused | Unsupervised

- Loss Inspector

- A monitoring tool of the validation loss change during training that guides you in training High Detail Modes (Red Analyze High Detail and Green Classify High Detail mode).

- F1 Score of Confusion Matrix for Red Analyze tools
  - The F1 score of the confusion matrix is introduced to show the result summary of the confusion matrix in Red Analyze tools.
  - Unlike the precision, recall, and F-score in Region Area Matrix which are calculated on a "pixel" basis, the F1 score of a confusion matrix is calculated from each "item in the confusion matrix table", aiming to suggest the performance of this tool with respect to the confusion matrix result.
- Auto Threshold for Red Analyze High Detail and Red Analyze Supervised
  - The T1 and T2 threshold values that maximize the F1 score of confusion matrix on Database Overview by following one of the 4 criteria in the Count dropdown menu. These threshold values are automatically calculated for you by enabling a checkbox.
- Region List for Red Analyze tools
  - The region list is introduced to help you find and check the defect regions (both labeled defects and markings) in a view more easily and conveniently and thus enhance your usability of Red Analyze tools.
- Overlay Checkbox
  - For all tools, the overlay checkbox is introduced for a handy alternative to "Cycle through Overlays" in the right-click pop-up menu on Image Display Area. See an example of the overlay checkbox for Blue Locate tool.
- Restore Parameters
  - For all tools, the restore parameter button is introduced for an easier "roll-back" of the set of parameter values in the Tool Parameter pane toward those that were used in the last training session. See an example of the restore parameters button for Blue Locate tool.

- Wibu CodeMeter Runtime update from 6.70a to 7.20b to resolve the known security vulnerabilities (WIBU-200521-01, WIBU-200521-02, WIBU-200521-03, WIBU-200521-05, WIBU-200521-06).

Note:

- The VisionPro, Designer and VisionPro Deep Learning software require that a valid Cognex Security Dongle be installed directly to PCs running the software during all phases of operation (programming, processing, training, testing, etc.). Any attempts to temporarily remove, substitute, or share a Cognex Security Dongle may cause your system to operate incorrectly, and may result in the loss of data.

  When VisionPro Deep Learning is configured for the Client/Server functionality, and a computer has been configured as a server, the Cognex Security Dongle must be attached to the server, but the client(s) does not need a Cognex Security Dongle.

- Sample code is included with the VisionPro Deep Learning 1.1.0 installer. The resources for the sample code (VisionPro Deep Learning 1.1 Sample Code Resource.msi), which include images and workspaces, are available for download from the Cognex Support Site.
- For more information about new API functionality in this release, see the Cognex VisionPro Deep Learning Suite .NET Library and Cognex VisionPro Deep Learning Suite C API help files.

# Introducing Cognex Deep Learning™

- VisionPro Deep Learning is Cognex’s new PC-based deep learning software product. It is the direct successor to VisionPro ViDi™. The first release of VisionPro Deep Learning adds a new “High Detail” mode to the existing ViDi Classifier, which is now known as “Focused” mode. High Detail mode was originally developed as part of the SuaKIT™ product. It provides highly accurate results for a wide range of challenging applications, while Focused mode typically trains and runs faster. Users can switch between modes without relabeling the images. This makes it easy to determine which mode offers the best combination of accuracy & speed for any particular application.

- VisionPro Deep Learning is compatible with VisionPro ViDi, including API, project loading and security dongles. Some changes have been made to Cognex Designer® support. See Using Runtime Workspace with Cognex Designer topic for details.

- SuaKIT users can import SuaKIT classification project into VisionPro Deep Learning 1.1. (VisionPro Deep Learning 1.1 doesn’t support the import of the other SuaKIT projects yet.). They can then take advantage of the other features of Cognex Deep Learning Studio, including the Blue Locate and OCR tools, tool chaining, and access to VisionPro® and Designer.