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    "slug": "cd-measurement-of-color-filters-cells",
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    "title": {
        "rendered": "CD Measurement of Color Filter\u2019s Cells"
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    "content": {
        "rendered": "<h4>Challenge<\/h4>\n<p>Given 64 semi-finished Bayer color filter images, which have only Green cells filled, we should measure the dimension of the filled central cell. The problem has the following challenges:<\/p>\n<ul>\n<li>Highly noisy images<\/li>\n<li>Low texture\/contrast<\/li>\n<li>High inter-class similarity<\/li>\n<li>Limited in quantity<\/li>\n<\/ul>\n<h4>Solution<\/h4>\n<p>Noise reduction technique was used to smooth the images. Unet deep learning then is applied to detect objects. Finally, draw and measure the bounding box of the detected objects.<\/p>\n<ul>\n<li>Unet works even in case the images have very bad quality<\/li>\n<li>Unet gives a high accuracy<\/li>\n<li>Unet requires fewer number of samples for training and testing data comparing with other models<\/li>\n<\/ul>\n<h4>Outcome<\/h4>\n<p>We were able to draw Larger and Smaller boundaries of the central cells at an accuracy that is equivalent to manual measurement done by experts.<\/p>",
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    "excerpt": {
        "rendered": "<p>Challenge Given 64 semi-finished Bayer color filter images, which have only Green cells filled, we should measure the dimension of the filled central cell. The problem has the following challenges: Highly noisy images Low texture\/contrast High inter-class similarity Limited in quantity Solution Noise reduction technique was used to smooth the images. Unet deep learning then [&hellip;]<\/p>",
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