Unity 1

Lesson: Object detection, image segmentation and convolutional neural network

Idiom of the day

Beta test: to start over or reset a situation. For example:

Meaning: Testing a product or service with a select group of users before releasing it to the general public.

Example: "The software is currently in beta testing, and we welcome feedback from users." 

Scanning strategy

Scanning in reading quickly identifies key information without reading every word, perfect for specific purposes or questions. Learn more by exploring the following resource.

Reading Activity: “What is object detection?”

Pay close attention to the following reading about machine learning and object detection.

Activities

After finishing the reading “What is object detection?”, answer the following questions.

Now, discuss the following questions with your partners.

Question 1

Can you think of situations in your daily life where object detection might be useful? How could recognizing and marking objects in images or videos make certain tasks easier? 

Question 2

What are some of your favorite technologies that involve recognizing things in pictures or videos? It could be from apps, cameras, or any other devices. How do you think these technologies work? 

Question 3

When you take a picture with your phone, have you ever wondered how it recognizes faces or objects? Let's discuss how you think this works and if it makes using your phone camera more enjoyable or convenient.

Video Activity “Object detection explained”

Watch the following video and answer the questions selecting the correct option.

Reading: “Image Segmentation: A comprehensive guide”

Pay close attention to the following reading about image segmentation.

Activity

Please, read the text once again!, and answer the following questions.

Watch the video: “What is a convolutional neural network (CNN)?”

Watch the following video and answer the questions selecting the correct option.

Kahoot: “What is a convolutional neural network (CNN)?”

Let's play and learn by clicking on the following Kahoot.

Now, discuss about the video the following questions with your partners:

How would you explain filters in Convolutional Neural Networks using an analogy from everyday life? Can you think of a comparison that someone who's not familiar with technology might understand? 

If you could invent a fun and creative application for filters in CNNs, what would it be? How might filters enhance the functionality or experience of this imaginative application? 

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