Easily Hide Data to the IOU

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A step-by-step guide on how to Hide Data to the IOU

Drag and drop your document to your Dashboard or add it from cloud storage services.
Use DocHub advanced PDF editing tools to Hide Data to the IOU.
Modify your document making more adjustments if necessary.
Include fillable fields and allocate them to a particular receiver.
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Generate reusable templates for frequently used documents.

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How to Hide Data to the IOU

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hey welcome back to this weeks video this is bill jelen uh this is hide sensitive data okay so heres a little report we have four authors uh working uh towards some books number of pages turned in this shows how many pages theyve turned in and their rank and we might want to kind of publish that little report but then off to the side over here uh you know the account in me uh put the the rate that were paying them per page and the total cost and i dont want that in the report so just a quick and dirty way to hide something is to use the white font all right so now we can create a pdf it doesnt show up but if i need it i just know that i can come over here select and all of a sudden that white font becomes visible so its there for me to see but as i create the pdf theyll never see that bit yeah we could hide columns but you know this is good if we just wanted to hide a few cells change the font to white and later on you can go back and find it but the people looking at the pdf f

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What is the IoU method?

Intersection over Union (IoU) is used when calculating mAP. It is a number from 0 to 1 that specifies the amount of overlap between the predicted and ground truth bounding box. IoU is an important accuracy measure to track when gathering human annotations.

What is the IoU in Matlab?

Intersection over union (IoU), also known as the Jaccard similarity coefficient, is the most commonly used metric. Use the IoU metric if you want a statistical accuracy measurement that penalizes false positives. The image describes the true positives (TP), false positives (FP), and false negatives (FN).

What is the need for semantic segmentation?

The goal of semantic segmentation is to partition an image into regions with different semantic categories.

What is the threshold for IoU?

IoU = Area of INTERSECTION /Area of UNION. IoU score 0.5 is considered as good.

Whats a good IoU score?

Note: 0.5 IoU is typically considered a good score, while 1 is perfect in theory. No matter where you get the ground-truth data or how carefully you label, its extremely unlikely to have the predicted output match the ground-truth bounding box coordinates.

What is the IoU for semantic segmentation?

Simply put, the IoU is the area of overlap between the predicted segmentation and the ground truth divided by the area of union between the predicted segmentation and the ground truth, as shown on the image to the left.

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