HomeQuestionsComputer ScienceIdentity Mapping in Deep Models
📚 Learning Guide
Identity Mapping in Deep Models
hard

You 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?

Master this concept with our detailed explanation and step-by-step learning approach

Learning Path
Learning Path

Question & Answer
1
Understand Question
2
Review Options
3
Learn Explanation
4
Explore Topic

Choose AnswerChoose the Best Answer

A

Use a linear activation function in all layers to ensure outputs are scaled down.

B

Implement skip connections that allow gradients to flow directly through the network without vanishing.

C

Increase the number of convolutional layers without any adjustments to the architecture.

D

Train the model without any form of regularization to maximize the capacity of the network.

Understanding the Answer

Let's break down why this is correct

Skip connections let the signal travel straight from one layer to another. Other options are incorrect because Using only linear activations keeps every layer a straight line; Adding more layers without any help makes the network harder to train.

Key Concepts

Identity Mapping
Deep Neural Networks
Residual Learning
Topic

Identity Mapping in Deep Models

Difficulty

hard level question

Cognitive Level

understand

Deep Dive: Identity Mapping in Deep Models

Master the fundamentals

Definition
Definition

Identity mapping is a technique used in constructing deeper models by adding layers that maintain the identity mapping from shallower models. This approach helps alleviate optimization challenges associated with increasing network depth and can lead to improved training error rates in very deep neural networks.

Topic Definition

Identity mapping is a technique used in constructing deeper models by adding layers that maintain the identity mapping from shallower models. This approach helps alleviate optimization challenges associated with increasing network depth and can lead to improved training error rates in very deep neural networks.

Ready to Master More Topics?

Join thousands of students using Seekh's interactive learning platform to excel in their studies with personalized practice and detailed explanations.

Start Learning with SeekhExplore More Identity Mapping in Deep Models Questions