Somaiya Vidyavihar University
K. J. Somaiya College of Engineering, Mumbai -77
(A Constituent College of Somaiya Vidyavihar University)
Course Code Course Title
116h59C701 Intelligent System
TH P TUT Total
Teaching
03 0 -- 03
Scheme(Hrs.)
Credits Assigned 03 0 -- 03
Marks
Examination CA
Scheme ESE TW O P P&O Total
ISE IA
30 20 50 -- -- -- 100
Course prerequisites:
Computer vision, Artificial Intelligence, Robotics
Course Objectives:
The course aims at developing students to make intelligent systems. Having gained knowledge in
the areas of Artificial Intelligence, Robotics, and Computer vision this course gives combined
exposure of all three on the application level.
Course Outcomes:
At the end of successful completion of the course, the student will be able to
CO1: Understand basic concepts of parallel computing.
CO2: Introduction to Compute Unified Device Architecture
CO3: Integrate AI with Robotics
CO4: Make an intelligent robot with computer vision integrated with it
CO5: Apply concepts of deep learning to real-time images and videos
Module Unit Details Hrs. CO
No. No.
1 Parallel Computing 9 CO1
1.1 Basics of parallel computing for accelerated computer
vision, Flynns classical Taxonomy, Parallel Computer
Memory Architecture, Parallel Programming Models,
Designing Parallel programmes, Distributed Systems.
2 Accelerated Computer Vision 9 CO2
2.1 Introduction to Compute Unified Device Architecture
(CUDA), CUDA architecture and applications, Working with
videos in OpenCV.
2.2 CUDA program structure, Threads, Synchronization,
and Memory. Application of Cuda and Open CV.
3 AI for Robotics 9 CO3
SVU2020- R1 ETRX_Honours Programme in AI, Computer Vision and Robotics Page 15 of 18
Somaiya Vidyavihar University
K. J. Somaiya College of Engineering, Mumbai -77
(A Constituent College of Somaiya Vidyavihar University)
3.1 Basic principle and designing process of AI robot,
OODA loop, Introduction to different AI-Robotic
paradigm, Hierarchical Paradigm,NHC, Reactive
Paradigms
SVU2020- R1 ETRX_Honours Programme in AI, Computer Vision and Robotics Page 16 of 18
Somaiya Vidyavihar University
K. J. Somaiya College of Engineering, Mumbai -77
(A Constituent College of Somaiya Vidyavihar University)
3.2 Designing a Reactive Behavioural System with case study,
Introduction to AI hardware processors, Advanced
robotics applications with AI (Autopilot planes,
Autonomous vehicles) Setting Up of AI Robot
4 Sensing Techniques and Intelligent Robotics with Applications of 9 CO4
CV
4.1 Model of sensing, Behavioral Sensors, Fusion
Sensors, Suite Proprioceptive Sensors, computer
vision sensing
4.2 introduction to Hybrid Paradigm of Robotic AI
Distributed mobile robot systems,
5 Computer Vision Applications with Deep Learning 9 CO5
5.1 Recognition in Computer Vision, Feature Extraction
Feature Selection & Reduction, Convolutional Neural
Networks, Derivation of Convolution , Designing a
CNN Recognition with artificial neural networks (ANN)
5.2 Tensor flow recognition, Graph Visualization Using
TB, Linear Model, Building FFNN, Recognition of
Images with deep learning
Total 45
Recommended Books:
Sr. No. Name/s of Author/s Title of Book Name of Edition and
Publisher with Year of
country Publication
1 Bhaumik Vaidya Hands-On GPU- Packt Publishing 1 Edition, Year
st
Accelerated Ltd, USA 2018
Computer Vision
with OpenCV
and CUDA
2 Francis X. Govers Artificial Packt Publishing 1 Edition, Year
st
Intelligence for Ltd, USA 2018
Robotics
3 Robin Murphy Introduction to MIT Press, USA 1 Edition, Year
st
AI Robotics 2000
4 Dominik Sankowski, Computer Vision World Scientific, 1 Edition, Year
st
Jacek Nowakowski In Robotics And USA 2014
Industrial
Applications
5 Ahmed Fawzy Gad Practical Apress 1 Edition, Year
st
Computer Vision publication USA 2018
Applications
Using Deep
Learning with
CNNs
SVU2020- R1 ETRX_Honours Programme in AI, Computer Vision and Robotics Page 17 of 18
Somaiya Vidyavihar University
K. J. Somaiya College of Engineering, Mumbai -77
(A Constituent College of Somaiya Vidyavihar University)
Course Code Course Title
116h59L701 Intelligent System Laboratory
TH P TUT Total
Teaching
0 02 -- 02
Scheme(Hrs.)
Credits Assigned 0 01 -- 01
Marks
Examination CA
Scheme ESE TW O P P&O Total
ISE IA
- - - 50 -- -- -- 50
Term-Work:
Term work will consist of experiments/ tutorials covering entire syllabus of the course
‘116h59C701’ . Students will be graded based on continuous assessment of their term
work
Course prerequisites: Linear algebra, Vector Calculus, Basic probability theory, Basic
Course prerequisites:
Programming Skills Linear algebra, Vector Calculus, Basic probability theory, Basic
Programming Skills
Course Objectives: The course aims to learn the fundamentals of Artificial Intelligence (AI), and
Course
apply Objectives:
them. The courseagents
Design intelligent aims to
to learn
solvethe fundamentals
real-world of Artificial
problems, FocusesIntelligence
on methods (AI),
for
and apply them. Design intelligent agents to solve real-world problems, Focuses on methods
deciding actions to be taken, representation of knowledge about the intelligent agents' environment for
deciding
with actions
reasoning and todecision
be taken,
makingrepresentation
in the presenceof knowledge about
of uncertainty the environment.
in the intelligent agents'
It also
discusses expert system solving problems efficiently and effectively based on knowledge ofinhuman
environment with reasoning and decision making in the presence of uncertainty the
environment. It also discusses expert system solving problems efficiently and effectively based
experts.
on knowledge of human experts.
Course Outcomes
Course Outcomes
At the end of successful completion of the course the student will be able to
At the end of successful completion of the course the student will be able to
CO1: Understand the idea of intelligent agents
CO1: Understand the idea of intelligent agents
CO2: Apply the search methods in AI.
CO2:Construct
CO3: Apply theplans
search
andmethods
methodsinfor
AI.generating knowledge
CO3: Construct plans and methods for generating knowledge
CO4: Understand the reasoning and decision making in an uncertain world.
CO4: Understand the reasoning and decision making in an uncertain world.
CO5: Understand the concepts of expert systems.
CO5: Understand the concepts of expert systems.
SVU2020- R1 ETRX_Honours Programme in AI, Computer Vision and Robotics Page 18 of 18
