Explain the Pattern. Pattern recognition and its application.
Pattern Recognition - Elective I Question Papers - SPPU University
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INSEM Papers for Pattern Recognition - Elective I
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Pattern Recognition - Elective I Questions
Pre-rendered question cards from available structured metadata.
2024 Nov Dec ENDSEM
2024 Sep INSEM
2024 Nov Dec ENDSEM
INSEM
2024 Sep INSEM
12 Questions
Q1
15 Marks
Q1
·
b
·
5 Marks
What are the different models or approaches of pattern recognition?
Q1
·
c
·
5 Marks
Explain feature extraction?
Q2
15 Marks
Q2
·
a
·
5 Marks
What is design cycle of pattern recognition?
Q2
·
b
·
5 Marks
What is Neural Pattern Recognition Approach?
Q2
·
c
·
5 Marks
Explain in details of Pattern Recognition System & what need of pattern recognition system.
Q3
15 Marks
Q3
·
a
·
5 Marks
Explain the statistical pattern recognition?
Q3
·
b
·
5 Marks
What are the different types of pattern classification?
Q3
·
c
·
5 Marks
What is an unsupervised learning approach in pattern recognition?
Q4
15 Marks
Q4
·
a
·
5 Marks
What is the Gaussian distribution classification?
Q4
·
b
·
5 Marks
What are discriminate function and its uses?
Q4
·
c
·
5 Marks
What are risk and errors in measurement of classification performance?
| Subject Name | Pattern Recognition - Elective I |
|---|---|
| Semester | I |
| Pattern Year | 2019 |
| Subject Code | 317522 (B) |
| Max Marks | 30 |
| Total Questions | 4 |
| Duration | 1 Hour |
| Paper Number | [6360]-131 |
| Academic Year | T.E. |
| Branch Name | Artificial Intelligence and Data Science |
| Exam Type | INSEM |
| Exam Session | 2024 Sep INSEM |
| Watermark | ['CEGP013091', '49.248.216.238 05/09/2024 10:59:37 static-238'] |
ENDSEM
2024 Nov Dec ENDSEM
16 Questions
Q1
17 Marks
Q1
·
a
·
9 Marks
Explain Blocks Word Description String Generation example as Pattern Description.
Q1
·
b
·
8 Marks
Describe an Abstract View of Parsing Problem?
Q2
17 Marks
Q2
·
a
·
9 Marks
Describe the Chomsky Normal form with suitable example.
Q2
·
b
·
8 Marks
Identify the different Elements of Formal Grammars.
Q3
17 Marks
Q3
·
a
·
9 Marks
Describe the Design and Selection of Similarity Measures.
Q3
·
b
·
8 Marks
Explain Clique finding algorithm with suitable example.
Q4
17 Marks
Q4
·
a
·
8 Marks
Distinguish between Homomorphism and Isomorphism.
Q4
·
b
·
9 Marks
Draw and Explain Grammatical Interface Model and its objective.
Q5
18 Marks
Q5
·
a
·
9 Marks
Describe with neat diagram Artificial Neuron Activation and Output Characteristics.
Q5
·
b
·
9 Marks
Describe the different reasons to adopt a Neural Computational Architecture.
Q6
18 Marks
Q6
·
a
·
9 Marks
Explain different Characteristics of Neural Computing Applications.
Q6
·
b
·
9 Marks
Describe CAM & other Neural Memory Structure.
Q7
18 Marks
Q7
·
a
·
9 Marks
Explain how the character classification is done with Pattern Associator?
Q7
·
b
·
9 Marks
Explain Summary of the Back Propagation learning Procedure with suitable diagram.
Q8
18 Marks
Q8
·
a
·
9 Marks
Draw & explain how to train the feedforward network using Generalized delta Rule?
Q8
·
b
·
9 Marks
Draw & Explain structure of a Multiple Layer Feedforward Network.
| Subject Name | Pattern Recognition - Elective I |
|---|---|
| Semester | I |
| Pattern Year | 2019 |
| Subject Code | 317522B |
| Max Marks | 70 |
| Total Questions | 8 |
| Duration | 2½ Hours |
| Paper Number | [6353]-55 |
| Academic Year | T.E. |
| Branch Name | Artificial Intelligence & Data Science |
| Exam Type | ENDSEM |
| Exam Session | 2024 Nov Dec ENDSEM |
| Watermark | ['CEGP013091', '49.248.216.237 19/12/2024 09:54:39 static-237'] |
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