Curriculum

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====== Object Detection ======

Machine learning approaches:
  * Viola–Jones object detection framework based on Haar features
  * Scale-invariant feature transform (SIFT)
  * Histogram of oriented gradients (HOG) features

Deep learning approaches:
  * Region-based Convolutinoal Neural Network (R-CNN) [[https://arxiv.org/abs/1311.2524 | 2014 Ross Girshick, et al, UC Berkeley]]
  * Single Shot MultiBox Detector (SSD)
  * You Only Look Once (YOLO) [[https://arxiv.org/abs/1506.02640 | 2015 Joseph Redmond et al]]
  * Single-Shot Refinement Neural Network for Object Detection (RefineDet)
  * Retina-Net
  * Deformable convolutional networks

Pre-trained models
  * COCO SSD MobileNet v1 model

Training from scratch
  * collect images
  * label images
  * run training
  * test effectiveness

Transfer Training
  * start with a pre-trained model
  * add your own images and labels

Python libraries with built-in object detection algorithms
  * OpenCV
  * TensorFlow

What is a model?
  * the output of a training session?
  * Data structure of a "model" or "network"?

Inference Graph?

[[YOLO]]

Pose Estimation
  - [[YOLO NAS POS]]