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Huawei HCIP-AI-EI Developer V2.5 Sample Questions:

1. Which of the following has never been used as a method in the history of NLP?

A) Rule-based method
B) Statistics-based method
C) Recursion-based method
D) Deep learning-based method

2. Maximum likelihood estimation (MLE) requires knowledge of the sample data's distribution type.

A) FALSE
B) TRUE

3. The jieba ------() method can be used for word segmentation.

4. In the image recognition algorithm, the structure design of the convolutional layer has a great impact on its performance. Which of the following statements are true about the structure and mechanism of the convolutional layer? (Transposed convolution is not considered.)

A) The convolutional layer slides over the input feature map using a convolution kernel of a fixed size to extract local features without explicitly defining their features.
B) A stride in the convolutional layer can control the spatial resolution of the output feature map. A larger stride indicates a smaller output feature map and simpler calculation.
C) In the convolutional layer, each neuron only collects some information. This effectively reduces the memory required.
D) The convolutional layer uses parameter sharing so that features at different positions share the same group of parameters. This reduces the number of network parameters required but reduces the expression capabilities of models.

5. Among image preprocessing techniques, gamma correction is a common non-linear brightness adjustment method. Which of the following statements are true about the application and features of gamma correction?

A) Gamma correction applies only to grayscale images and does not apply to color images.
B) When # < 1, the input high grayscale range is compressed, and the low grayscale range is stretched, enhancing the dark areas while compressing the bright areas.
C) When # > 1, the input low grayscale range is compressed, and the high grayscale range is stretched, enhancing the bright areas while compressing the dark areas.
D) Gamma correction is an enhancement technique based on exponential transformation mapping. It is used for non-linear contrast stretching.

Solutions: