Analyzing Images with Computer Vision
Computer vision is one of the fields in which deep learning has progressed enormously, surpassing human-level performance in several tasks such as image classification and object recognition. Furthermore, the field has moved from academia to real-world applications, and the industry is recognizing its practitioners as adding high value to businesses.
In this chapter, we will learn how to use GluonCV, a MXNet Gluon library specific to computer vision, how to build our own networks, and how to use GluonCV’s model zoo to use pretrained models for several applications.
Specifically, we will cover the following topics:
- Understanding convolutional neural networks
- Classifying images with AlexNet and ResNet
- Detecting objects with Faster R-CNN and YOLO
- Segmenting objects in images with PSPNet and DeepLab-v3
