Learning Path
Question & Answer1
Understand Question2
Review Options3
Learn Explanation4
Explore TopicChoose the Best Answer
A
It allows for deeper networks without increasing complexity
B
It prevents overfitting by reducing the number of parameters
C
It facilitates the gradient flow by providing shortcuts
D
It eliminates the need for activation functions entirely
Understanding the Answer
Let's break down why this is correct
Answer
Identity mapping means that a layer can simply pass its input straight through without changing it, acting like a shortcut. During training, this allows the gradient to flow directly back to earlier layers, preventing the “vanishing gradient” problem that usually slows learning in very deep nets. By giving the network a path that keeps the signal unchanged, it can focus on learning useful differences rather than struggling to learn an identity from scratch. For example, if a 50‑layer network includes identity shortcuts, the error from the last layer can reach the first layer almost unchanged, making weight updates faster and more stable. This makes the network easier to optimize and often results in better performance.
Detailed Explanation
Identity mapping adds a shortcut that lets the gradient travel directly from later layers back to earlier ones. Other options are incorrect because The idea that identity mapping reduces complexity is a misconception; Identity mapping does not shrink the model.
Key Concepts
Identity Mapping
Deep Neural Networks
Residual Learning
Topic
Identity Mapping in Deep Models
Difficulty
medium level question
Cognitive Level
understand
Practice Similar Questions
Test your understanding with related questions
1
Question 1What is the primary purpose of identity mapping in deep learning models?
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2
Question 2How can identity mapping in deep neural networks enhance business applications such as customer segmentation and predictive analytics?
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3
Question 3In the context of deep learning, how can identity mapping enhance business applications while facilitating the scaling of models?
hardComputer-science
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4
Question 4A team of developers is working on a very deep neural network for image classification. They notice that as they add more layers, the training accuracy starts to decrease. To address this issue, they decide to implement identity mapping. How does this technique help improve the training process in their model?
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5
Question 5How does identity mapping in deep models primarily benefit the training of neural networks?
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6
Question 6Identity Mapping in deep learning models is to optimizing training as a navigation system is to _____?
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7
Question 7Arrange the following steps in the process of implementing identity mapping in deep neural networks to optimize training: A) Add identity mapping layers, B) Train the network with residual connections, C) Initialize weights for deeper layers, D) Evaluate performance on training data.
mediumComputer-science
Practice
8
Question 8You are designing a deep neural network to improve image recognition accuracy. Which of the following strategies would best utilize identity mapping to address common issues of training deep networks?
hardComputer-science
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9
Question 9In the context of deep learning, identity mapping is primarily used to maintain the ________ from shallower models, aiding in the training of deeper networks.
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10
Question 10Why does identity mapping in deep neural networks help improve training performance in very deep models?
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Practice
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