Computer vision is a field of artificial intelligence and computer science that focuses on enabling computers to interpret and understand visual information from images or videos. It involves developing algorithms and models to extract meaningful information and make inferences from visual data.
This competency area includes an understanding of the concepts of transfer learning, data augmentation, object detection, and model optimization.
- Transfer Learning - Understanding the basic concepts of transfer learning to fine-tune pre-trained models for new tasks.
- Data Augmentation - Understanding the basic concepts for data augmentation and how to apply them to improve model performance.
- Object Detection - Understanding the basic concepts of object detection models such as Faster R-CNN and YOLO and how to use pre-trained models.
- Model Optimization - Knowledge of advanced regularization techniques such as dropout, batch normalization, and weight decay.