#1
Which deep learning architecture is often used for image classification tasks?
ResNet
LSTM (Long Short-Term Memory)
Gated Recurrent Unit (GRU)
K-Means
#2
What is the role of the activation function in a neural network?
To calculate the loss function
To control the learning rate
To introduce non-linearity to the network
To preprocess input images
#3
Which technique is commonly used for image denoising?
K-Means clustering
Sobel operator
Gaussian blur
Hough transform
#4
Which deep learning framework is commonly used for computer vision tasks?
TensorFlow
PyTorch
Keras
Scikit-learn
#5
What does the acronym CNN stand for in the context of deep learning?
Centralized Neural Network
Complex Neural Network
Convolutional Neural Network
Continuous Neural Network
#6
What is the basic purpose of image segmentation in computer vision?
To classify images
To detect objects in images
To divide an image into meaningful segments
To enhance image resolution
#7
Which algorithm is commonly used for object detection in images?
K-Means
Decision Trees
Random Forest
YOLO (You Only Look Once)
#8
In image processing, what does the term 'Histogram' represent?
A graphical representation of pixel intensities in an image
The process of colorizing grayscale images
A type of image compression technique
A measure of image resolution
#9
Which technique is commonly used for image feature extraction?
Principal Component Analysis (PCA)
Fuzzy Logic
Genetic Algorithms
Naive Bayes Classifier
#10
Which type of neural network architecture is suitable for sequential data, such as time series or text?
Convolutional Neural Network (CNN)
Recurrent Neural Network (RNN)
Generative Adversarial Network (GAN)
Autoencoder
#11
What is the purpose of non-maximum suppression in object detection?
To increase the number of detected objects
To reduce false positives and keep only the most confident predictions
To decrease the model training time
To enhance image quality
#12
What is the significance of anchor boxes in object detection algorithms?
To weigh the importance of different objects
To define the spatial locations of potential objects in an image
To store labeled images for training
To optimize loss functions
#13
What is the purpose of data augmentation in image processing?
To reduce model complexity
To increase the size of the training dataset by applying transformations
To remove noise from images
To adjust the learning rate dynamically
#14
What is the primary advantage of transfer learning in image classification?
It allows the model to learn from scratch
It enables the reuse of pre-trained models on a new task
It reduces the need for labeled training data
It speeds up the training process
#15
In the context of image recognition, what does the term 'F1 score' measure?
Model training time
Precision and recall balance
Image resolution
Learning rate