- Deep Learning for Vision Systems
- Copyright
- dedication
- contents
- front matter
- Part 1. Deep learning foundation
- 1 Welcome to computer vision
- 2 Deep learning and neural networks
- 3 Convolutional neural networks
- 4 Structuring DL projects and hyperparameter tuning
- 4.1 Defining performance metrics
- 4.2 Designing a baseline model
- 4.3 Getting your data ready for training
- 4.4 Evaluating the model and interpreting its performance
- 4.5 Improving the network and tuning hyperparameters
- 4.6 Learning and optimization
- 4.7 Optimization algorithms
- 4.8 Regularization techniques to avoid overfitting
- 4.9 Batch normalization
- 4.10 Project: Achieve high accuracy on image classification
- Summary
- Part 2. Image classification and detection
- 5 Advanced CNN architectures
- 6 Transfer learning
- 6.1 What problems does transfer learning solve?
- 6.2 What is transfer learning?
- 6.3 How transfer learning works
- 6.4 Transfer learning approaches
- 6.5 Choosing the appropriate level of transfer learning
- 6.5.1 Scenario 1: Target dataset is small and similar to the source dataset
- 6.5.2 Scenario 2: Target dataset is large and similar to the source dataset
- 6.5.3 Scenario 3: Target dataset is small and different from the source dataset
- 6.5.4 Scenario 4: Target dataset is large and different from the source dataset
- 6.5.5 Recap of the transfer learning scenarios
- 6.6 Open source datasets
- 6.7 Project 1: A pretrained network as a feature extractor
- 6.8 Project 2: Fine-tuning
- Summary
- 7 Object detection with R-CNN, SSD, and YOLO
- Part 3. Generative models and visual embeddings
- 8 Generative adversarial networks (GANs)
- 9 DeepDream and neural style transfer
- 10 Visual embeddings
- appendix A. Getting set up
- index
dedication
To my mom, Huda, who taught me perseverance and kindness To my dad, Ali, who taught me patience and purpose To my loving and supportive wife, Amanda, who always inspires me to keep climbing To my two-year-old daughter, Emily, who teaches me every day that AI still has a long way to go to catch up with even the tiniest humans
-
No Comment
..................Content has been hidden....................
You can't read the all page of ebook, please click here login for view all page.