Exam Details
| Subject | Pattern Recognition | |
| Paper | ||
| Exam / Course | B.Tech In Computer Science And Engineering (BTCSVI) | |
| Department | School of Engineering & Technology (SOET) | |
| Organization | indira gandhi national open university | |
| Position | ||
| Exam Date | June, 2016 | |
| City, State | new delhi, |
Question Paper
No. of Printed Pages: 3 IBICSE-OlS!
B.Tech. -VIEP -COMPUTER SCIENCE AND ENGINEERING (BTCSVI)
Term-End Examination 00436
June, 2016
BICSE-O18 PATTERN RECOGNITION
Time hours Maximum Marks: 70
Note: Answer any seven questions. All questions carry equal marks.
1. Describe the terms 'pattern' and 'pattern recognition'. What are the various techniques for recognizing the pattern Give a brief outline of each technique. What are the applications of pattern recognition techniques in different domains? 10
2. Discuss the role of edge detection algorithms in pattern recognition. What are the stages in edge detection mechanism Describe each stage. Describe the 'Pattern Fit Approach' for edge detection. 10
3. Compare and contrast any two of the following: 5+5=10
Supervised learning and Unsupervised learning
Edge detection and Edge linking
Regular patterns and Irregular patterns
4. Identify the parameters used to describe the boundary. Discuss each identified parameter in detail. Explain anyone boundary detection algorithm. 10
5. Briefly discuss any two of the following mechanisms: 5+5=10
Boundary matching
Boundary merging
Boundary segmentation
6. Discuss any two of the following classifiers, with their role in pattern recognition: 5+5=10
Fuzzy classifier
Statistical classifier
Neural classifier
7. What is clustering? Discuss the role of clustering in pattern recognition. Explain anyone category of clustering algorithm. 10
8. What are neural networks? Discuss the working of neural networks with a suitable diagram. How do neural networks contribute to recognize any pattern Give a suitable example in support of your answer. 10
9. Explain the traditional snake model in locating object contours. 10
10. Write short notes on any two of the following (give suitable example for each) 5+5=10
Statistical pattern recognition
Syntactic pattern recognition
Clustering
B.Tech. -VIEP -COMPUTER SCIENCE AND ENGINEERING (BTCSVI)
Term-End Examination 00436
June, 2016
BICSE-O18 PATTERN RECOGNITION
Time hours Maximum Marks: 70
Note: Answer any seven questions. All questions carry equal marks.
1. Describe the terms 'pattern' and 'pattern recognition'. What are the various techniques for recognizing the pattern Give a brief outline of each technique. What are the applications of pattern recognition techniques in different domains? 10
2. Discuss the role of edge detection algorithms in pattern recognition. What are the stages in edge detection mechanism Describe each stage. Describe the 'Pattern Fit Approach' for edge detection. 10
3. Compare and contrast any two of the following: 5+5=10
Supervised learning and Unsupervised learning
Edge detection and Edge linking
Regular patterns and Irregular patterns
4. Identify the parameters used to describe the boundary. Discuss each identified parameter in detail. Explain anyone boundary detection algorithm. 10
5. Briefly discuss any two of the following mechanisms: 5+5=10
Boundary matching
Boundary merging
Boundary segmentation
6. Discuss any two of the following classifiers, with their role in pattern recognition: 5+5=10
Fuzzy classifier
Statistical classifier
Neural classifier
7. What is clustering? Discuss the role of clustering in pattern recognition. Explain anyone category of clustering algorithm. 10
8. What are neural networks? Discuss the working of neural networks with a suitable diagram. How do neural networks contribute to recognize any pattern Give a suitable example in support of your answer. 10
9. Explain the traditional snake model in locating object contours. 10
10. Write short notes on any two of the following (give suitable example for each) 5+5=10
Statistical pattern recognition
Syntactic pattern recognition
Clustering
Other Question Papers
Departments
- Centre for Corporate Education, Training & Consultancy (CCETC)
- Centre for Corporate Education, Training & Consultancy (CCETC)
- National Centre for Disability Studies (NCDS)
- School of Agriculture (SOA)
- School of Computer and Information Sciences (SOCIS)
- School of Continuing Education (SOCE)
- School of Education (SOE)
- School of Engineering & Technology (SOET)
- School of Extension and Development Studies (SOEDS)
- School of Foreign Languages (SOFL)
- School of Gender Development Studies(SOGDS)
- School of Health Science (SOHS)
- School of Humanities (SOH)
- School of Interdisciplinary and Trans-Disciplinary Studies (SOITDS)
- School of Journalism and New Media Studies (SOJNMS)
- School of Law (SOL)
- School of Management Studies (SOMS)
- School of Performing Arts and Visual Arts (SOPVA)
- School of Performing Arts and Visual Arts(SOPVA)
- School of Sciences (SOS)
- School of Social Sciences (SOSS)
- School of Social Work (SOSW)
- School of Tourism & Hospitality Service Sectoral SOMS (SOTHSM)
- School of Tourism &Hospitality Service Sectoral SOMS (SOTHSSM)
- School of Translation Studies and Training (SOTST)
- School of Vocational Education and Training (SOVET)
- Staff Training & Research in Distance Education (STRIDE)
Subjects
- Advanced Computer Architecture
- Artificial Intelligence
- Computer Architecture
- Computer Networks
- Computer Organisations
- Cryptography And Network Security
- Data Structure
- Data Warehousing And Mining
- Database Management System
- Design and Analysis of Algorithm
- Digital Image Processing
- Discrete Maths Structure
- E-Business
- Formal Language And Automata
- Logic Design
- Microprocessor
- Mobile Computing
- Object Oriented Programming
- Operating Systems
- Parallel Algorithms
- Pattern Recognition
- Principles of Programming Lang.
- Real Time Systems
- Software Engineering
- Software Quality Engineering
- Software Reusability
- System Programming And Compiler Design
- Theory Of Computation
- Unix Internals And Shell Programming
- Web Technology