Learning Path
Question & Answer1
Understand Question2
Review Options3
Learn Explanation4
Explore TopicChoose the Best Answer
A
It increases the number of parameters without affecting the model's ability to learn.
B
It allows gradients to flow more easily through the network during backpropagation.
C
It reduces the complexity of the model by removing layers.
D
It ensures that each layer learns unique features independently.
Understanding the Answer
Let's break down why this is correct
Answer
Identity mapping, often added as a shortcut or skip connection, lets a deep network simply pass its input forward unchanged, so the signal can travel unchanged from one layer to the next. This means that gradients can flow back through many layers without being multiplied by small or large numbers, which prevents vanishing or exploding gradients and keeps the learning signal strong. Because the network can choose to keep the identity mapping or gradually change it, training starts with a very easy solution and then slowly learns more complex functions. For example, a 100‑layer network that can skip 10 layers at a time can learn quickly because the early layers don’t have to learn a new representation from scratch; they only refine the identity mapping. Thus, identity mapping stabilizes training and makes very deep models trainable.
Detailed Explanation
Identity mapping lets the input signal pass straight through layers. Other options are incorrect because Adding more parameters does not guarantee better learning; Identity mapping does not remove layers; it adds extra connections that skip layers.
Key Concepts
Identity Mapping
Deep Neural Networks
Backpropagation
Topic
Identity Mapping in Deep Models
Difficulty
easy 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?
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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 6How does identity mapping in deep neural networks help with optimization during training?
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7
Question 7Identity Mapping in deep learning models is to optimizing training as a navigation system is to _____?
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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?
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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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