Vishwakarma Institute of Technology
Issue 05 : Rev No. 0 : Dt. 13/03/15
Course Plan Format
Academic Year : 2015-16
FF No. 182
Branch : Electronics, E&TC
Semester : I
Subject Name : Pattern Recognition
Subject Code: EC 42103, EC 42203
Unit
No.
I
Topic
Method
Media
Machine
perception,
Pattern Lecture
recognition systems, design cycle,
learning and adaptation.
Board – Chalk
II
Bayesian
Decision
theory Lecture
continuous and discrete features,
minimum error rate classification,
classification discriminant function,
Parameter estimation methods like
Maximum-Likelihood estimation,
Gaussian
mixture
models,
Expectationmaximization method,
and Bayesian estimation.
Board – Chalk
III
Parzen-window method, K-Nearest Lecture
Neighbour method, metrics and
NearestNeighbor Classification.
Board – Chalk
Student Activity
Assessment Tool
Tut: Questions based i)TestI: Explanation
on
Concept
of type questions – 100
pattern recognition % weitage
and
Machine ii)Timely submission
of completed home
perception.
assignment
iii)Tutorial assessment
is based on MCQ
based questions: one
before Test II and
other before ESE
Tut: Analysis of i) MCQ based Test II
Bayesian Decision ii)Timely submission
theory
continuous of completed home
and discrete features, assignment
Analysis
of iii)Tutorial assessment
is based on MCQ
Maximumbased questions: one
Likelihood
before Test II and
estimation
other before ESE
 Matlab
based
execution of the
tutorial
Tut: Analysis of i) MCQ based Test II
Minimum Distance ii)Timely submission
Classifier,
Parzen of completed home
assignment
Remarks
Test I out of 30
marks, to be
converted to 10
marks
Test II out of 20
marks, to be
converted to 20
marks
Vishwakarma Institute of Technology
Issue 05 : Rev No. 0 : Dt. 13/03/15
Windows
and iii)Tutorial assessment
is based on MCQ
Neighbour method
 Matlab
execution
tutorial
IV
Linear discriminant function and Lecture
decision
surface,
Perceptron,
Support vector machines
Board – Chalk
V
Criterion functions for clustering, Lecture
Algorithms for clustering: Kmeans, Hierarchical and other
methods,
Cluster
validation,
component analysis.
Board – Chalk
based based questions: one
of the before Test II and
other before ESE
Tut: Analysis of i)Timely submission
Linear discriminant of completed home
function, Analysis of assignment
Support
vector ii)Tutorial assessment
is based on MCQ
machines
based questions: one
before Test II and
other before ESE
Tut: Analysis of i)Timely submission
Algorithms
for of completed home
assignment
clustering
ii)Tutorial assessment
is based on MCQ
based questions: one
before Test II and
other before ESE
Levels of Bloom’s Taxonomy applicable for the course – Knowledge / Comprehension / Application / Analysis / Synthesis / Evaluation (Strike out levels not applicable)
List of Reference Books and Text Books -
1. Pattern Classification, R.O.Duda, P.E.Hart and D.G.Stork, John Wiley, 2001
2. Pattern Recognition, S.Theodoridis and K.Koutroumbas, 4th Ed., Academic Press, 2009
3. Pattern Recognition and Machine Learning, C.M.Bishop, Springer, 2006
#§◘■□-
Details of laboratory course student activity for experiments based on appropriate unit.
Details of Tutorial course student activity based on appropriate unit.
Mandatory Assessment activities as per structure.
Mode of conduct of class test is to be mentioned.
Scope of HA should be written in brief.
Write unit-wise parameters used for continuous assessment of laboratory course.
Vishwakarma Institute of Technology
○-
Issue 05 : Rev No. 0 : Dt. 13/03/15
If parameters are used as a whole, they may be described in footer.
Write unit-wise parameters used for continuous assessment of tut. course.
Name and Signature of Faculty executing the course plan
1)
P. A. Kulkarni
2)
_____________________________________________
3)
_____________________________________________
…….
…….
Signature of Chairman – BOS
Date : 28 / 3 / 2015