#1
What is OCR an abbreviation for in the context of letter recognition?
#2
Which of the following is NOT a typical challenge in letter recognition?
#3
What is the term used to describe the process of dividing a dataset into training and testing sets for evaluating a letter recognition model?
#4
In letter recognition, what does OCR stand for?
#5
Which of the following is NOT a challenge faced in letter recognition?
#6
In the context of letter recognition, what is the term used to describe the process of converting an image of a letter into digital form?
#7
Which of the following machine learning algorithms is commonly used for letter recognition tasks?
#8
What type of neural network architecture is frequently employed for handwritten letter recognition?
#9
Which of the following techniques is commonly used for feature extraction in letter recognition tasks?
#10
What is the term used to describe the process of adjusting the weights of a neural network during training to minimize errors?
#11
Which of the following is a popular programming library used for implementing neural networks in Python for letter recognition tasks?
#12
Which statistical technique is often used to preprocess data for letter recognition by reducing its dimensionality while preserving important information?
#13
What is the name of the dataset commonly used for benchmarking letter recognition algorithms, which contains 20,000 examples of 20 English alphabet letters, each represented by 16x16 pixels?
#14
Which of the following evaluation metrics is commonly used to assess the performance of a letter recognition system?
#15
Which of the following methods is commonly used to handle imbalanced classes in letter recognition datasets?
#16
Which of the following activation functions is commonly used in the hidden layers of a neural network for letter recognition?
#17