MCQ IN COMPUTER SCIENCE & ENGINEERING

Detailed explanation-1: -On the basis of survey, pattern recognition techniques can be categorized into six parts. These include Statistical Techniques, Structural Techniques, Template Matching, Neural Network Approach, Fuzzy Model and Hybrid Models.

Detailed explanation-2: -The trained and tested model developed for recognizing patterns using machine learning algorithms is called a classifier. This classifier is used to make predictions for unseen data/objects.

Detailed explanation-3: -Pattern recognition is a data analysis method that uses machine learning algorithms to automatically recognize patterns and regularities in data. This data can be anything from text and images to sounds or other definable qualities. Pattern recognition systems can recognize familiar patterns quickly and accurately.

Detailed explanation-4: -For pattern recognition, the most common method is feed-forward networks, which means that there is no feedback to the input. As humans learn from their past experiences and mistakes, such networks also learn from their mistakes by giving feedback to the input patterns.