Object detection and tracking using deep learning

1. What is object tracking in deep learning?
2. Is object detection part of deep learning?
3. Can we use CNN for object detection?
4. Which CNN model is best for object detection?

What is object tracking in deep learning?

Object tracking is a deep learning process where the algorithm tracks the movement of an object. In other words, it is the task of estimating or predicting the positions and other relevant information of moving objects in a video. Object tracking usually involves the process of object detection.

Is object detection part of deep learning?

Object detection is a computer vision technique for locating instances of objects in images or videos. Object detection algorithms typically leverage machine learning or deep learning to produce meaningful results.

Can we use CNN for object detection?

The faster region convolutional neural network [15] is another state-of-the-art CNN-based deep learning object detection approach. In this architecture, the network takes the provided input image into a convolutional network which provides a convolutional feature map.

Which CNN model is best for object detection?

R-CNN – Region-based Convolutional Neural Networks

Region-based convolutional neural networks or regions with CNN features (R-CNNs) are pioneering approaches that apply deep models to object detection.