What is the primary advantage of using a Convolutional Neural Network (CNN) over a standard feed-forward neural network for image classification tasks?
- CNNs can automatically learn hierarchical features from images
- CNNs require fewer training examples than feed-forward networks
- CNNs have a simpler architecture than feed-forward networks
- CNNs are less computationally intensive than feed-forward networks
Convolutional Neural Networks (CNNs) excel in image tasks due to their ability to automatically learn hierarchical features like edges, textures, and shapes. This hierarchical feature learning makes them more effective in image classification tasks.
Loading...
Related Quiz
- Which term describes a model that has been trained too closely to the training data and may not perform well on new, unseen data?
- A medical diagnosis AI system provides a diagnosis but does not give any rationale or reasoning behind it. What aspect of machine learning is this system lacking?
- A financial institution wants to predict whether a loan applicant is likely to default on their loan. They have a mix of numerical data (like income, age) and categorical data (like occupation, marital status). Which algorithm might be well-suited for this task due to its ability to handle both types of data?
- A retail store wants to recommend products to customers based on their purchase history. They want to find products that other customers with similar purchase histories have bought. Which algorithm is apt for this recommendation system?
- One of the drawbacks of using t-SNE is that it's not deterministic, meaning multiple runs with the same data can yield ________ results.