K-NN match for object recognition

1. Which neural network is best for object detection?
2. Which method is best for object detection?
3. What is the best way to choose K for KNN?
4. What does K 3 mean in KNN?

Which neural network is best for object detection?

Most Popular Object Detection Algorithms. Popular algorithms used to perform object detection include convolutional neural networks (R-CNN, Region-Based Convolutional Neural Networks), Fast R-CNN, and YOLO (You Only Look Once). The R-CNN's are in the R-CNN family, while YOLO is part of the single-shot detector family.

Which method is best for object detection?

– RetinaNet is currently one of the best methods for object detection in a number of different tasks. It can be used as a replacement for a single-shot detector for a multitude of tasks to achieve quick and accurate results for images.

What is the best way to choose K for KNN?

The optimal K value usually found is the square root of N, where N is the total number of samples. Use an error plot or accuracy plot to find the most favorable K value.

What does K 3 mean in KNN?

If k=1, then test examples are given the same label as the closest example in the training set. If k=3, the labels of the three closest classes are checked and the most common (i.e., occuring at least twice) label is assigned, and so on for larger ks.