Class 10 AI Chapter - Computer Vision Topic - Question/Answer - Arvindzeclass

Class 10 Artificial Intelligent Code 417 Solutions

Session 2025-26

Artificial Intelligence code 417 syllabus pdf class 10 solutions. Class 10 AI Book. Part - A, Part - B, and Python. This article provides complete solution for class 10 AI (Artificial Intelligence) Code - 417 solution according to new syllabus 2025 – 26. In this article first of all go through the AI Code - 417 syllabus and then follow chapter wise notes. Class 10 AI MCQs Quiz with answers.

Part A - Employability Skills Question/Answers

Chapter 1 -Communication Skills - II

Chapter 2 -Self - Management Skills - II

Chapter 3 - ICT Skills - II

Chapter 4 - Entrepreneurial Skills - II

Chapter 5 - Green Skills - II

Part B - Subject Specific Skills Question/Answers

Chapter 1 -AI Project Cycle & Ethics

Chapter 2 - Modelling in AI

Chapter 3 - Evaluating Models

Chapter 4 - Statistical Data

Chapter 5 - Computer Vision

Chapter 6 - Natural Language Processing

Chapter 7 - Advance Python

#What is Computer Vision Tasks?

A. Single Object Tasks

These tasks assume only ONE main object in the image.

1. Image Classification

The model identifies what the object is.

Input: image with a single object
Output: the label (name/object category)

Example:
Image → 🐶
Output → “Dog”

There is no location information, only the category.

2. Classification + Localization

The model identifies what the object is AND where it is located.

It gives two outputs:
1. The category (e.g., “Dog”)
2. The bounding box (the rectangle around the object)

Example:
Image → 🐶 in a garden
Output → “Dog at these coordinates (x,y,w,h)”

This still assumes one main object, but also marks its position.

B. Multiple Object Tasks

In these tasks, the image contains many objects of different types, and the model must identify each one separately.

3. Object Detection

Detects all objects in the image and draws a bounding box around each of them.

Output:
- Object class (what it is)
- Bounding box (where it is)

Example:
Image → road scene
Output → “Car”, “Person”, “Traffic light”, each with its own box.

However, object detection doesn’t understand object shape, only boxes.

4. Instance Segmentation

Detects and outlines each object pixel-by-pixel, not just a box.

It is more detailed than object detection.
Also distinguishes different instances of the same object.

Example:
If there are 3 people:

Instance segmentation gives three separate masks (shape outlines)
Not just three boxes

This is used in self-driving cars, medical imaging, AR, etc.

Summary Table

Category	Task	Purpose	Output
Single Object	Classification	What is it?	Label only
Single Object	Classification + Localization	What & Where?	Label + box
Multiple Objects	Object Detection	What & Where (for ALL)	Labels + boxes
Multiple Objects	Instance Segmentation	Exact shape & position	Labels + pixel-level masks