Evaluate the impact of an AI application used in the real world. (case study) : Working with X-Ray images: Case Study -

The video tutorial discusses handling large image sizes, particularly gray images without RGB channels. It emphasizes the importance of mindful data augmentation, avoiding techniques like vertical flipping or center cropping that could distort data. The tutorial also covers preprocessing methods, including feature-wise centering, standard normalization, and rescaling, to prepare images for training models.

What is a key difference between the current images and those used in the flower data project?

• The current images are smaller in size.

• The current images are in color.

• The current images have a third channel.

• The current images are grayscale.

Why might cropping the center of an image be problematic in this context?

• It adds unnecessary noise.

• It changes the color balance.

• It could remove important anomalies.

• It makes the image too large.

Which data augmentation technique is considered acceptable for the current images?

• Horizontal flip

• Vertical flip

• Center cropping

• Upside down rotation

What is the purpose of feature-wise centering in preprocessing?

• To convert images to grayscale

• To normalize the image data

• To adjust image brightness

• To increase image size

What is the next step after preprocessing the data?

• Model evaluation

• Data augmentation

• Rescaling the images

• Feature extraction