KaaShiv's Training Program will provide you with in-depth knowledge in MATLAB
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Topic | Text Material | Image content | Video content | Quiz |
---|---|---|---|---|
Image Acquisition | - | |||
Applications of Digital Image Processing | - | |||
Image Enhancement in the Spatial Domain | - | |||
Point Operations | - | |||
Histogram Processing | - | |||
Thresholding | - | |||
Neighborhood Operations | - | |||
MATLAB - Introduction | - | |||
MATLAB - Environment Setup | - | |||
MATLAB - Basic Syntax | - | |||
MATLAB - Variables | - | |||
MATLAB - Commands | - | |||
MATLAB - M-Files | - | |||
MATLAB - Data Types | - | |||
MATLAB - Operators | - | |||
MATLAB - Decision Making | - | |||
Digital Image Representation | - | |||
Image Types | - |
Topic | Text Material | Image content | Video content | Quiz |
---|---|---|---|---|
MATLAB - Loop Types | - | |||
MATLAB - Vectors | - | |||
MATLAB - Matrix | - | |||
MATLAB - Arrays | - | |||
MATLAB - Colon Notation | - | |||
MATLAB - Numbers | - | |||
MATLAB - Strings | - | |||
Fourier Analysis | - | |||
The 1-D Discrete Fourier Transform | - | |||
The 2-D Discrete Fourier Transform | - | |||
DFT Representation of Images | - | |||
Computation of the 2-D DFT | - | |||
Properties of the 2-D DFT | - | |||
The 2-D Fourier Transform | - | |||
Intensity Transformation Functions | - | |||
Histogram Processing and Function Plotting | - | |||
Spatial Filtering | - |
Topic | Text Material | Image content | Video content | Quiz |
---|---|---|---|---|
MATLAB - Functions | - | |||
MATLAB - Data Import | - | |||
MATLAB - Data Output | - | |||
MATLAB - Plotting | - | |||
MATLAB - Graphics | - | |||
MATLAB - Algebra | - | |||
Image Enhancement in the Frequency Domain | - | |||
1-D Linear Convolution Using the DFT | - | |||
2-D Linear Convolution Using the DFT | - | |||
Lowpass Filtering | - | |||
The Laplacian Filter | - | |||
Frequency-Domain Filters | - | |||
Homomorphic Filtering | - | |||
Image Processing Toolbox Standard Spatial Filters | - | |||
Using Fuzzy Techniques for Intensity Transformations and Spatial Filtering | - |
Topic | Text Material | Image content | Video content | Quiz |
---|---|---|---|---|
The 1-D Fourier Transform | - | |||
Image Restoration | - | |||
The Image Restoration Process | - | |||
Inverse Filtering | - | |||
Wiener Filter | - | |||
The 2-D Wiener Filter | - | |||
Image Degradation Model | - | |||
Characterization of the Noise and Its Reduction | - | |||
Filtering in the Frequency Domain | - | |||
Obtaining Frequency Domain Filters from Spatial Filte | - |
Topic | Text Material | Image content | Video content | Quiz |
---|---|---|---|---|
MATLAB - Calculus | - | |||
MATLAB - Differential | - | |||
MATLAB - Integration | - | |||
MATLAB - Polynomials | - | |||
MATLAB - Transforms | - | |||
MATLAB - GNU Octave | - | |||
MATLAB - Simulink | - | |||
Geometric Transformations and Image Registration | - | |||
Interpolation | - | |||
Affine Transform | - | |||
Correlation | - | |||
Image Registration | - | |||
Image Reconstruction from Projection | - | |||
The Normal Form of a Line | - | |||
The Radon Transform | - | |||
Hough Transform | - |
Topic | Text Material | Image content | Video content | Quiz |
---|---|---|---|---|
Matlab - Classes and Objects | - | |||
MatLab- User Classes | - | |||
MatLab - Timer Object | - | |||
MatLab - Timer Object Properties | - | |||
MatLab - Memory Usage | - | |||
MatLab - Resolving Out of Memory Errors | - | |||
MatLab- M-File Functions | - | |||
MatLab - Debugging | - | |||
MatLab - Audio and Video Files | - | |||
MatLab - Path | - | |||
Morphological Image Processing | - | |||
Binary Morphological Operations | - | |||
Binary Morphological Algorithms | - | |||
Grayscale Morphology | - | |||
Edge Detection | - | |||
Edge Detection Matlab | - | |||
Canny Edge Detection Algorithm | - | |||
Laplacian of Gaussian | - | |||
Segmentation | - | |||
Edge-Based Segmentation | - | |||
Threshold-Based Segmentation | - | |||
Region-Based Segmentation | - | |||
Watershed Algorithm | - | |||
Object Description | - | |||
Boundary Descriptors | - | |||
Regional Descriptors | - | |||
Principal Component Analysis | - |
Topic | Text Material | Image content | Video content | Quiz |
---|---|---|---|---|
Object Classification | - | |||
The k-Nearest Neighbors Classifier | - | |||
The Minimum-Distance-to-Mean Classifier | - | |||
Decision-Theoretic Methods | - | |||
Decision Tree Classification | - | |||
Bayesian Classification | - | |||
k-Means Clustering matlab | - | |||
Image Compression | - | |||
Lossless Compression | - | |||
Transform-Domain Compression | - | |||
Image Compression with Biorthogonal Filters | - | |||
Color Models | - | |||
Pseudocoloring | - | |||
Color Image Processing matlab | - |
MATLAB is a programming language developed by MathWorks. It started out as a matrix programming language where linear algebra programming was simple. It can be run both under interactive sessions and as a batch job. This internship gives you aggressively a gentle introduction of MATLAB programming language. It is designed to give students fluency in MATLAB programming language. Problem-based MATLAB examples have been given in simple and easy way to make your learning fast and effective.
This internship has been prepared for the beginners to help them understand basic to advanced functionality of MATLAB. After completing this internship you will find yourself at a moderate level of expertise in using MATLAB from where you can take yourself to next levels.
We assume you have a little knowledge of any computer programming and understand concepts like variables, constants, expression, statements, etc. If you have done programming in any other high-level programming language like C, C++ or Java, then it will be very much beneficial and learning MATLAB will be like a fun for you.
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We have a lifetime 24x7 online support team to resolve all your technical queries, through a ticket based tracking system.
Successfully complete your final course project and Kaashiv will certify you as a MATLAB Expert.
We have a community forum for all our learners that further facilitates learning through peer interaction and knowledge