Computer Vision: Exploring AI and ML Applications

Question 1

Which of the following is not a typical application of computer vision?

Accepted Answer

Natural language processing

Answer

Object detection

Answer

Image classification

Answer

Facial recognition

Question 2

Which of these is **NOT** a typical use of computer vision?

Accepted Answer

Understanding natural language

Answer

Identifying objects in images

Answer

Diagnosing medical images

Answer

Recognizing faces

Question 3

What is **not** a fundamental part of a computer vision system?

Accepted Answer

Data saving and archiving

Answer

Image capture and preparation

Answer

Feature identification and description

Question 4

In computer vision, which of these is NOT a feature descriptor?

Accepted Answer

Mean pixel intensity

Answer

Histogram of Oriented Gradients (HOG)

Answer

Scale-Invariant Feature Transform (SIFT)

Answer

Speeded Up Robust Features (SURF)

Question 5

Which of the following is NOT a fundamental task in computer vision?

Accepted Answer

Text generation

Answer

Object detection

Answer

Image classification

Answer

Facial recognition

Question 6

In image classification, what type of deep learning model is commonly employed?

Accepted Answer

Convolutional Neural Network (CNN)

Answer

Support Vector Machine (SVM)

Answer

Linear Regression Model

Answer

Recurrent Neural Network (RNN)

Question 7

What technique is used to subdivide an image into smaller, manageable regions?

Accepted Answer

Image segmentation

Answer

Feature extraction

Answer

Object recognition

Answer

Image classification

Question 8

What is the process of obtaining significant features from an image known as?

Accepted Answer

Feature extraction

Answer

Facial recognition

Answer

Image classification

Answer

Object detection

Question 9

Which computer vision application is used in the medical field?

Accepted Answer

Medical image analysis

Answer

Face detection in social media

Answer

Self-driving cars

Question 10

In object detection, what is the purpose of a bounding box?

Accepted Answer

Describes the location and size of a detected object

Answer

Categorizes the detected object

Answer

Extracts features from the detected object

Question 11

What is the primary contribution of deep learning to computer vision?

Accepted Answer

Automating feature extraction and object recognition

Answer

Providing human-like image comprehension

Answer

Enhancing the accuracy of traditional machine learning models

Question 12

Which of the following is NOT a key application of computer vision?

Accepted Answer

Natural language translation

Answer

Object detection

Answer

Image recognition

Question 13

What is the primary goal of an image segmentation algorithm in computer vision?

Accepted Answer

To divide an image into regions with similar visual characteristics

Answer

To generate synthetic images based on real-world data

Answer

To detect and classify objects within an image

Question 14

Which type of machine learning algorithm is primarily used for object detection in computer vision?

Accepted Answer

Convolutional Neural Network (CNN)

Answer

Linear regression

Answer

Decision tree

Answer

k-Nearest Neighbors (k-NN)

Question 15

What is the purpose of a feature extractor in a computer vision system?

Accepted Answer

To identify and extract relevant visual features from an image

Answer

To store and manage large datasets of images

Answer

To train and update machine learning models

Question 16

How has deep learning impacted computer vision?

Accepted Answer

Enabled the creation of powerful image recognition and object detection models

Answer

Increased the speed of processing large image datasets

Answer

Provided the theoretical basis for computer vision algorithms

Question 17

What is the fundamental principle behind image recognition in computer vision?

Accepted Answer

Matching extracted image features to known patterns

Answer

Storing and comparing every possible image

Answer

Using AI to interpret the semantic meaning of images

Question 18

How does computer vision contribute to the development of autonomous vehicles?

Accepted Answer

Enables vehicles to perceive and navigate their surroundings

Answer

Provides real-time traffic updates

Answer

Improves fuel efficiency and reduces emissions

Question 19

What is the significance of ground truth data in computer vision?

Accepted Answer

It provides accurate labels for training and evaluating models

Answer

It reduces the computational cost of training computer vision models

Answer

It ensures that computer vision algorithms are unbiased

Question 20

Which of the following is NOT a key application of Computer Vision in real-world scenarios?

Accepted Answer

Weather Forecasting

Answer

Object Detection

Answer

Medical Image Analysis

Answer

Facial Recognition

Question 21

What is the primary task of a Deep Convolutional Neural Network (DCNN) in computer vision?

Accepted Answer

Feature Extraction

Answer

Data Storage

Answer

Image Generation

Answer

Object Classification

Question 22

Which of the following is a key challenge in Object Detection using Computer Vision?

Accepted Answer

Occlusion

Answer

Low Resolution

Answer

Noise

Answer

Blur

Question 23

What is the difference between Supervised and Unsupervised Learning in Computer Vision?

Accepted Answer

Labeled vs. Unlabeled Data

Answer

Algorithm Complexity

Answer

Time Required for Training

Answer

Accuracy of Results

Question 24

What is the main goal of Image Segmentation in Computer Vision?

Accepted Answer

Assigning Pixels to Objects or Regions

Answer

Image Classification

Answer

Feature Extraction

Answer

Object Detection

Question 25

What is the primary purpose of image segmentation in computer vision?

Accepted Answer

To divide an image into meaningful regions of interest

Answer

To remove noise from an image

Answer

To enhance the contrast of an image

Question 26

Which type of deep learning architecture is commonly used for computer vision tasks?

Accepted Answer

Convolutional Neural Network (CNN)

Answer

Decision Tree

Answer

Support Vector Machine (SVM)

Answer

Recurrent Neural Network (RNN)

Question 27

What is the main goal of object detection in computer vision?

Accepted Answer

To locate and identify objects within an image

Answer

To extract features from an image

Answer

To segment an image into foreground and background

Answer

To classify images into predefined categories

Question 28

Which of the following techniques is primarily used for facial recognition?

Accepted Answer

Eigenfaces

Answer

K-Nearest Neighbors

Answer

Random Forest

Answer

Linear Regression

Question 29

What is the crucial role of training data in computer vision systems?

Accepted Answer

To train the system to recognize patterns and make accurate predictions

Answer

To store the results of previous image processing operations

Answer

To calibrate the camera used for image capture

Question 30

Identify a potential application of computer vision in the healthcare industry.

Accepted Answer

Disease diagnosis and analysis

Answer

Customer relationship management

Answer

Financial forecasting

Answer

Supply chain management

Question 31

Discuss the potential ethical implications of using computer vision systems for surveillance purposes.

Accepted Answer

Potential violations of privacy and concerns regarding discrimination

Answer

Improved public safety

Answer

Increased efficiency in law enforcement

Question 32

In computer vision, which technique plays a crucial role in detecting objects within images?

Accepted Answer

Convolutional Neural Networks (CNNs)

Answer

Linear Regression

Answer

Support Vector Machines

Answer

Natural Language Processing (NLP)

Question 33

What is the primary purpose of image segmentation in the context of computer vision?

Accepted Answer

Partitioning an image into segments based on similar characteristics

Answer

Classifying images into predefined categories

Answer

Identifying objects within images

Question 34

In real-world applications, facial recognition technology is commonly used for:

Accepted Answer

Access control and security systems

Answer

Sentiment analysis and emotion detection

Answer

Predictive analytics and forecasting

Answer

Medical diagnosis and analysis

Question 35

What is the key advantage of using transfer learning in computer vision models?

Accepted Answer

Leveraging pre-trained models to enhance performance on new tasks

Answer

Eliminating the requirement for model optimization

Answer

Reducing the need for extensive data collection

Question 36

What is the fundamental role of deep learning in computer vision?

Accepted Answer

Enabling computers to learn complex patterns and derive insights from data

Answer

Storing and managing large volumes of image data

Answer

Providing explicit rules and instructions for image interpretation

Question 37

In computer vision, which metric is commonly used to assess the effectiveness of object detection models?

Accepted Answer

Mean Average Precision (mAP)

Answer

Root Mean Squared Error (RMSE)

Answer

F1-score

Answer

Accuracy

Question 38

What is the primary purpose of employing augmentation techniques in computer vision?

Accepted Answer

Enhancing the diversity of the training dataset and improving model generalization

Answer

Accelerating the training process

Answer

Reducing the size of the training dataset

Question 39

What are some ethical considerations associated with the use of computer vision technology?

Accepted Answer

Privacy concerns, potential for bias, and misuse

Answer

Increased employment opportunities

Answer

Enhanced accessibility for individuals with disabilities

Answer

Improved public safety and security

Question 40

What is the primary objective of computer vision?

Accepted Answer

To empower computers with the ability to 'see' and comprehend images and videos.

Answer

To facilitate the development of self-driving vehicles.

Answer

To enhance the accuracy of weather forecasts.

Question 41

In the realm of image recognition, which technique is commonly employed?

Accepted Answer

Convolutional Neural Networks (CNNs)

Answer

Support Vector Machines

Answer

Decision Trees

Answer

Linear Regression

Question 42

What is the objective of feature extraction within the context of computer vision?

Accepted Answer

To minimize the dimensionality of the data while extracting pertinent information.

Answer

To expedite the computational process.

Answer

To enhance the interpretability of the data.

Question 43

Which application of computer vision is utilized in the medical field for diagnostic purposes?

Accepted Answer

Medical image analysis

Answer

Virtual reality

Answer

Self-driving cars

Answer

Facial recognition

Question 44

Describe how facial recognition operates in the realm of computer vision.

Accepted Answer

Facial features are mapped to identify individuals uniquely.

Answer

Measurement of distances between facial landmarks.

Answer

Analysis of voice patterns.

Question 45

What are the ethical considerations that computer vision raises?

Accepted Answer

Concerns about privacy, bias, and potential misuse.

Answer

Legal implications and data ownership.

Answer

Computational cost and energy consumption.

Answer

Limited accuracy and reliability.

Question 46

Identify a limitation associated with computer vision.

Accepted Answer

Susceptibility to noise, variations in lighting, and occlusions.

Answer

Exceptional accuracy and reliability in all circumstances.

Answer

Universal applicability to all image and video data.

Question 47

Explain the role of computer vision in robotics.

Accepted Answer

To empower robots with the ability to navigate, manipulate objects, and interact with their environment.

Answer

To enhance security and surveillance capabilities.

Answer

To enable the development of autonomous weapons systems.

Question 48

Describe the significance of deep learning in the field of computer vision.

Accepted Answer

Enables computers to learn complex patterns and representations directly from data.

Answer

Provides a theoretical basis for computer vision algorithms.

Answer

Improves the efficiency of conventional image processing algorithms.

Question 49

Which emerging trend is currently gaining prominence in computer vision research?

Accepted Answer

Generative Adversarial Networks (GANs)

Answer

Bayesian inference

Answer

Quantum computing

Question 50

Which of the following is NOT a typical application of computer vision?

Accepted Answer

Generating realistic speech

Answer

Analysing medical images for diagnosis

Answer

Enabling self-driving cars

Answer

Recognising faces for security purposes

Question 51

Which type of machine learning is most commonly used for image recognition?

Accepted Answer

Supervised learning

Answer

Reinforcement learning

Answer

Unsupervised learning

Answer

Evolutionary learning

Question 52

Which algorithm is commonly used to detect edges and boundaries within images?

Accepted Answer

Canny edge detection

Answer

Support Vector Machine (SVM)

Answer

Principal Component Analysis (PCA)

Answer

K-means clustering

Question 53

What is the main purpose of using Convolutional Neural Networks (CNNs) in computer vision?

Accepted Answer

Extracting features from images

Answer

Predicting stock market trends

Answer

Generating synthetic data

Answer

Classifying text documents

Question 54

In computer vision, what does 'object detection' refer to?

Accepted Answer

Locating and classifying objects within an image

Answer

Identifying different colours in an image

Answer

Converting a colour image to grayscale

Answer

Enhancing the resolution of an image

Question 55

What is a significant challenge faced by facial recognition technology?

Accepted Answer

Variations in lighting and facial expressions

Answer

Limited computational power available

Answer

Lack of available data for training

Answer

Inability to process colour images

Question 56

What is the role of a 'dataset' when training a computer vision model?

Accepted Answer

It provides labelled images for the model to learn from

Answer

It generates new images to expand the training data

Answer

It evaluates the performance of the trained model

Answer

It stores the code of the computer vision algorithms

Question 57

How does computer vision contribute to the development of self-driving cars?

Accepted Answer

It allows cars to 'see' and understand their surroundings

Answer

It controls the engine and braking systems of the car

Answer

It communicates with other vehicles on the road

Answer

It provides the navigation system with GPS coordinates

Question 58

What is a major ethical concern related to facial recognition technology?

Accepted Answer

Potential for bias and discrimination

Answer

Lack of skilled professionals in the field

Answer

Difficulty in integrating with existing systems

Answer

High energy consumption of the algorithms

Question 59

What is the key difference between image recognition and image segmentation?

Accepted Answer

Image recognition identifies objects, while segmentation outlines their boundaries within the image

Answer

Image recognition processes colour images, while segmentation works on grayscale images

Answer

Image recognition is a simpler task than image segmentation

Answer

Image recognition is used in robotics, while segmentation is primarily for medical imaging