Which of the following statements are true about the differences between using convolutional neural networks (CNNs) in text tasks and image tasks?

• A. For CNN, there is no difference in handling text or image tasks.
• B. Color image input is multi-channel, whereas text input is single-channel.
• C. CNNs are suitable for image tasks, but they perform poorly in text tasks.
• D. When the CNN is used for text tasks, the kernel size must be the same as the number of word vector dimensions. This constraint, however, does not apply to image tasks.

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. In the convolutional layer, each neuron only collects some information. This effectively reduces the memory required.
• B. 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.
• C. 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.
• D. 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.

Which of the following applications are supported by ModelArts ExeML?

• A. Anomalous sound detection in production or security scenarios
• B. Automatic offering classification
• C. Predictive maintenance of manufacturing equipment
• D. Dress code conformance monitoring in campuses

Maximum likelihood estimation (MLE) can be used for parameter estimation in a Gaussian mixture model (GMM).

• A. FALSE
• B. TRUE