Feature walk-through: Improved interaction between your classification/quantification models and the image data
Modeling and data analysis
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Improved the interaction between models and image data, making easier to add new training data, retrain models and view the results on your image
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Apply models on images directly in the Record Study table
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Include, exclude or balance new training samples and then retrain models
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Update categories and properties data from model prediction results
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ONNX models inference performance improvements
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Constrained spectral unmixing with new options for Scatter correction parameter "None" and method for "Sum To One Least Squares" Unmixing (descriptor) Unmixing (segmentation)
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Better naming for the different machine learning algorithms
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More statistics in the classification confusion matrix (f-score, precision and recall)
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Prediction summary (Observed vs Predicted) for quantification analysis through right-click in Table
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Pre-treatment option to use SNV in the Explore tab
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Use multiple spectral ranges for SAM (Spectral Angle Mapper) Spectral angle mapper (SAM) guide
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Balance model with included train data or all train data
Image segmentation
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Deep Learning Image Segmentation (Faster R-CNN and Yolo4/5) applied to pseudo RGB or model predicted image ONNX image segmentation
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Image segmentation using YOLOv5
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K-Means clustering as method for selecting representative spectrum Representative spectrum
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Add samples to Manual segmentation through right-click in Table
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Object filter for segmentation (ex. object shape)
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Summary table showing pixel overlap of multiple segmentations
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Setting for Max number of objects in Deep Learning Image Segmentation
Visualization
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Pixels on an object that are excluded in the segmentation (e.g. holes showing the background) are also excluded in the visualizations (Pixel Explore, Table thumbnail)
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Merge all samples in segmentation now show all merged samples as one object in the preview image and in Table
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Change RGB bands by right clicking on image
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Test scan show % saturated bands
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Selected samples in Pixel Explore can be highlighted in Table and vice versa
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Option for Quantification model to predict and show value for individual pixels or only object average
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Change direction of real time visualization (horizontal or vertical)
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Option to show all or individual segmentation in Table if there are multiple segmentations on the same level
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Select multiple samples in preview image by holding down the shift key and making rectangular selection of the area with the mouse
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Yellow color for added class in Classification summary (confusion matrix)
Workflow
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Disable nodes in Analyse Tree that should not be used
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Export and import Breeze models into your study
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White and dark reference descriptor (signal intensity value)
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Metadata descriptor for each image (ex. image length and resolution)
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Delete workflow command in Breeze Runtime
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Access Study settings in Analyse Tree on Measurement node
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Link multiple segmentations to one output
Data acquisition
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Stray light correction option in Settings
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Saturation descriptor for maximum value and percent saturated band per pixel
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Explore pixel spectra on images in Test Scan
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Indication that new white or dark reference will be taken when recording using reference cache
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Set integration time in Record wizard
General ease-of-use improvements
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Duplicate Study with option to include all measurements and data
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Move measurement to another Group in the same Study
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Improved help sections for Segmentations , Descriptors and Actions
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New tutorial and data included: Classification of plastics Plastic Classification