H13-321_V2.5 Exam Dumps : HCIP - AI EI Developer V2.5 Exam

Morphological processing in image analysis is used to process binary or grayscale images based on shape.

Dilation:Expands object boundaries, useful for filling small holes.

Erosion:Shrinks object boundaries, useful for removing noise.By combining them:

Opening:Erosion followed by dilation (removes small objects/noise).

Closing:Dilation followed by erosion (fills small holes).

Exact Extract from HCIP-AI EI Developer V2.5:

"Morphological processing is based on dilation and erosion. Opening and closing are composite operations derived from these two to handle noise removal and hole filling."

TheTransformerarchitecture introduced in 2017 eliminates recurrence (RNN) and convolution entirely, relying solely on self-attention mechanisms and feed-forward layers. It does not contain LSTM or CNN components, which distinguishes it from previous sequence models.

Exact Extract from HCIP-AI EI Developer V2.5:

"The Transformer architecture does not use RNNs or CNNs. It relies entirely on self-attention and feed-forward networks for sequence modeling."

In NLP:

Text classification(e.g., sentiment analysis) predicts a single label for the entire input sequence.

Sequence labeling(e.g., Named Entity Recognition, Part-of-Speech tagging) produces an output label for each token or position in the input sequence.This distinction is important for selecting appropriate model architectures and loss functions.

Exact Extract from HCIP-AI EI Developer V2.5:

"Text classification assigns one label to the whole text, whereas sequence labeling assigns a label to each token in the sequence."