Data Science and Machine Learning (Theory and Projects) A to Z - Object Detection: Hand Engineering Versus CNNs

The video discusses classical computer vision techniques, emphasizing the difference between hand-engineered methods and convolutional neural networks (CNNs). It explains the challenges of high-dimensional feature spaces and the need for large datasets, known as the curse of dimensionality. The video highlights the trade-offs between hand engineering and deep learning, depending on data availability. It introduces CNNs as a powerful tool for image classification and object detection, capable of learning features automatically, reducing the need for manual feature design.

What role does the availability of data play in choosing between classical techniques and deep learning?

How do convolutional neural networks learn features automatically?

What are some applications of convolutional neural networks beyond image classification?