Object Detection

Object detection - Wikipedia #ril

Methods
- Methods for object detection generally fall into either MACHINE LEARNING-BASED approaches or DEEP LEARNING-BASED approaches.
  
  For Machine Learning approaches, it becomes necessary to first DEFINE FEATURES?? using one of the methods below, then using a technique such as SUPPORT VECTOR MACHINE (SVM) to do the CLASSIFICATION.
  
  On the other hand, deep learning techniques that are able to do END-TO-END object detection without specifically defining features, and are typically based on convolutional neural networks (CNN) (卷積神經網路).
- 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 Proposals (R-CNN, Fast R-CNN, Faster R-CNN)
  - Single Shot MultiBox Detector (SSD)
  - You Only Look Once (YOLO)
How we teach computers to understand pictures | Fei Fei Li - YouTube

參考資料 {: #reference }

ImageNet

更多：

YOLO
SSD

相關：