Classical image analysis is a process where particles of interest are segregated from the rest by means of hand-designed methods such as thresholding (deciding whether to keep or discard a pixel based on its numerical value) or the watershed algorithm (viewing the image as a topographic map and successively grouping pixels based on height). These methods require some amount of manual correction to mitigate noise or false detection depending on the complexity of the image. How can we improve data collection?
In this webinar, you will hear leading imaging experts, Darren McHugh and Girish Mallya, from Innopharma Technology illustrate what Convolutional Neural Network (CNN) is and how it offers users the ability to create a software model that emulates human vision, thereby offering robust, automated, and accurate particle segmentation. You will gain confidence in the CNN-powered image processing for features such as particle size and shape.
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