About the Program
This program has been initiated to enhance the knowledge from beginner to advance for the people who are interested in learning of advanced technologies like Machine Learning and neural networks. Other than learning, this program also provides an industrial exposure of working in this software and the toolbox with its relevant Algorithms. This program provides a comprehensive introduction to practical machine learning using MATLAB. In this hands-on program you will learn how to perform machine learning Algorithms using MATLAB. Also you will learn the fundamentals of deep learning and understand terms like “layers”, “networks”, and “loss” functions.
Technologies and Tools Covered
- MATLAB Toolbox and Programming
- Image Processing
- Neural Network
- Basics of Image Processing & Matlab Toolboxes
This session will encourage learning what ML is, what can be done with ML, and how to start creating ML Algorithms. The combination of theory with practical exercises will be conduct.
|1||Overview of Image Processing|
|2||Image Processing Techniques and Concepts|
|3||Matlab Programming & GUI Creation|
|4||Working on filtering Techniques and Gray & HSV Conversions|
|6||Edge detection Algorithm Implementation|
|7||Image Classification Implementation|
II. Machine Learning Concepts & Algorithms using Matlab
Introduction to the concepts of Machine Learning in MATLAB will be dealt with simple programs by the participants. This shall serve as the first step into the advanced concepts implementation in Deep Learning and AI by using MATLAB.
|1||Machine Learning Concepts and Methodologies|
|2||Neural Network Algorithms and the Working Principle|
|3||Mathematical Expression of Neural Network|
|4||Algorithms in Machine Learning & Limitation of Machine Learning|
Projects & Assignments
Practical 1 : Image Pre-processing & Applying Transformation
Practical 2 : Image Segmentation
Practical 3 : Edge Detection
Practical 4 : GUI Development
Practical 5 : Image Classification Implementation
Practical 6 : Neural Network Algorithms
The Program is mix of Theory sessions, Quizzes, Hands on Sessions, Liver Interaction with Experts, Assignments and Practical Exercises. Maximum Impetus is given to Hands on Sessions so as to enable the participants with the maximum knowledge transfer and satisfaction. The ratio of the theory, practical sessions will be 30:70.
· Code with Explanations
Learn everything about Image Processing and the Matlab toolboxes, with a well-structured curriculum & detailed explanation with code.
Work on various assignments which will be graded by our Trainer.
Solve real world problems as part of projects and receive valuable feedback from our trainer.
Upon Successful Completion of the Program
Upon completion of the program, the participant will have an in-depth insight into the Image Processing, Algorithms and Machine Learning Concepts. The participants will be able to program the controller and develop basic / complex applications on his own, thus making the objective of the training program as desired.
Participants also will have access to our TECHNICAL FORUM, thus getting their doubts clarified even after the session is complete. Certificates will be provided upon request.
Module 1: MATLAB Programming – Installation, Features & Tool Box
MATLAB Introduction - Installation of MATLAB - Matrices in MATLAB – Functions in MATLAB - Save & Load Variables in MATLAB – Graphs & Plotsin MATLAB – Customising Plots - Graphical User Interface in MATLAB - Creating Buttons in GUI.
Introduction to MATLAB Programming & Functions
MATLAB Commands - Control Statements – Loops in MATLAB (For, IF, While) – Loading Images – Basic Conversions - Introduction to Filters - Graphical User Interface in MATLAB (Level II) - Creating Other Specifications (GUI)
Module 2: Image Fundamentals & Image Processing Techniques
Types of Images – Import – Visualize and Extract Information from Images – Sampling & Quantisation of Images – RGB Conversion – Gray Scale Conversion of Images – Discrete Wavelet Transform – Discrete Fourier Transform
Module 3: Image Pre Processing & De Noising using Filters
Image Enhancement – Image Blurring & De Blurring – Transformation – Image Erosion – Dilation & Fusion Techniques – Application Demo
De Noising & Filtering Images
Noise Estimation - Noise Reduction – Spatial Filters (Mean & Adaptive Filters) & Frequency Domain Filters (Band Pass Filters) – Noise reduction in Image (Demo & Hands On)
Module 4: Compression Techniques of Images in MATLAB
Compression Concept - Image Coding & Decoding Model - Lossless & Lossy Compression – DWT & DFT Based Compression – SWT Based Compression –Watermarking- Applications of Image Compression - MATLAB
Module 5: Application of GLCM in Image Processing
Compressed Images - Fundamentals of Feature Extraction in Images – GLCM Introduction & Application Analysis
Module 6: Image Segmentation & Detection
Image Segmentation – Concepts – Binary Based Image Segmentation – K Means Based Image Segmentation - Spatial Fuzzy Means clustering of Image Segmentation- Segmenting based on Colour – Region based segmentation - Hands on Exercises
Module 7: Detection, Cryptography and Data Hiding in Images
Finding & Analysing Objects in Images – Detecting Shapes & Edges in Images – Canny Edge Detection Image Encryption – Decryption – AES Algorithm based Image encryption – RSA algorithm based Encryption – Data Hiding Examples
Internship Review It was really a great experience !!!!
With daily practice and assignments, we sure did expanded our understanding of DIP using MATLAB
It was a nice experience learning this course. Never used Matlab before but now I know about various tools and how to use them. Our mentor was excellent.
Most of the content in this is already in few of our accadamic syllabus (image processing).So apart form that basic lot more to learn. If you felt interested in image processing mainly in matlab a good for starter pack.good and clean.