Dragonfly Daily 20 Segmentation Trainer with Dragonfly (2020) скачать в хорошем качестве

Dragonfly Daily 20 Segmentation Trainer with Dragonfly (2020)

Hosted by Mike Marsh, Dragonfly Product Manager at ORS Download and Get Started with Dragonfly https://www.theobjects.com/dragonfly/... This is lesson 20 in an ongoing daily tutorial series that teaches new users how to become Dragonfly experts in no time. This lesson introduces users to Segmentation Trainer with Dragonfly Watch the Playlist with all of the Dragonfly Daily tutorials on YouTube http://orss.ca/ytp2 Topics of this lesson 1-One or more input images 2-Two or more out ROIs 3-Tailored feature vector to discriminate pixels into different ROIs 4-Can work on pixels or on super pixels 5-Training -Less training data is required, compared to Deep Learning -Different machine learning models are supported (e.g. Random Forest, Adaboost, etc.) -Training is not cumulative 6-Trained models persist on machine -Can be shared and re-trained Let's Connect 🡆 Twitter-   / orsdragonfly3d   🡆 LinkedIn:   / object-research-systems   🡆 ORS Website: ORS Website: https://www.theobjects.com 🡆 Sales-related inquiries: sales@theobjects.com 🡆 Support: support@theobjects.com About ORS Object Research Systems (ORS) develops deep learning powered 3D visualization and image analysis software. Dragonfly and Dragonfly Cloud, ORS’ flagship products, provide innovators from leading universities or industries, an advanced machine learning and neural networks based segmentation engine. Dragonfly's quantification tools then provide powerful options for counting, measuring, and characterizing image features, such as pores, fibers, grains, and much more. Its user-fVideo details - YouTube Studioriendly experience translates its powerful and accurate quantitative findings in high-impact visuals. The ability to build fully automated workflows also enables reproducible results #Dragonfly #MachineLearning #Segmentation #microscopy #imagesegmentation #microCT #FIBSEM #scientificimaging #electronmicroscopy #imageprocessing