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

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

Assessment

Interactive Video

Information Technology (IT), Architecture

University

Hard

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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.

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3 questions

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1.

OPEN ENDED QUESTION

3 mins • 1 pt

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

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2.

OPEN ENDED QUESTION

3 mins • 1 pt

How do convolutional neural networks learn features automatically?

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3.

OPEN ENDED QUESTION

3 mins • 1 pt

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

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