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Modern Computer Vision with PyTorch. Explore deep learning concepts and implement over 50 real-world image applications

Modern Computer Vision with PyTorch. Explore deep learning concepts and implement over 50 real-world image applications

V Kishore Ayyadevara, Yeshwanth Reddy

Ebook
Deep learning is the driving force behind many recent advances in various computer vision (CV) applications. This book takes a hands-on approach to help you to solve over 50 CV problems using PyTorch1.x on real-world datasets.
You’ll start by building a neural network (NN) from scratch using NumPy and PyTorch and discover best practices for tweaking its hyperparameters. You’ll then perform image classification using convolutional neural networks and transfer learning and understand how they work. As you progress, you’ll implement multiple use cases of 2D and 3D multi-object detection, segmentation, human-pose-estimation by learning about the R-CNN family, SSD, YOLO, U-Net architectures, and the Detectron2 platform. The book will also guide you in performing facial expression swapping, generating new faces, and manipulating facial expressions as you explore autoencoders and modern generative adversarial networks. You’ll learn how to combine CV with NLP techniques, such as LSTM and transformer, and RL techniques, such as Deep Q-learning, to implement OCR, image captioning, object detection, and a self-driving car agent. Finally, you'll move your NN model to production on the AWS Cloud.
By the end of this book, you’ll be able to leverage modern NN architectures to solve over 50 real-world CV problems confidently.
  • 1. Artificial Neural Network Fundamentals
  • 2. PyTorch Fundamentals
  • 3. Building a Deep Neural Network with PyTorch
  • 4. Introducing Convolutional Neural Networks
  • 5. Transfer Learning for object Classification
  • 6. Practical Aspects of Image Classification
  • 7. Basics of Object detection
  • 8. Advanced object detection
  • 9. Image segmentation
  • 10. Applications of object detection and localization
  • 11. Autoencoders and Image Manipulation
  • 12. Image generation using GAN
  • 13. Advanced GANs to manipulate images
  • 14. Training with minimal data points
  • 15. Combining Computer Vision and NLP techniques
  • 16. Combining Computer Vision and Reinforcement Learning
  • 17. Moving a Model to Production
  • 18. OpenCV utilities for image analysis
  • Tytuł: Modern Computer Vision with PyTorch. Explore deep learning concepts and implement over 50 real-world image applications
  • Autor: V Kishore Ayyadevara, Yeshwanth Reddy
  • Tytuł oryginału: Modern Computer Vision with PyTorch. Explore deep learning concepts and implement over 50 real-world image applications
  • ISBN: 9781839216534, 9781839216534
  • Data wydania: 2020-11-27
  • Format: Ebook
  • Identyfikator pozycji: e_2ai4
  • Wydawca: Packt Publishing