Monthly Archives: April 2020

Tutorials

spring.io

Building an Application with Spring Boot

IBM

What is Java Spring Boot?
Spring Boot basics

Microsoft Azure

Spring vs. Struts

Difference Between Spring and Struts in Java: What’s the Best Choice?
GeeksForGeeks Spring vs. Struts in Java
Spring vs Struts – Difference Between Spring and Struts

GitHub

github.com/in28minutes/learn, Amazing Cloud, Full Stack and Microservice Courses and Videos from in28Minutes

YouTube

Java Brains

What is the Spring framework really all about?
What is the difference between frameworks and libraries?
Spring Tutorial 01 – Understanding Dependency Injection

Spring Security Basics

What is Spring Security really all about?
Five Spring Security Concepts – Authentication vs authorization
Adding Spring Security to new Spring Boot project
How to configure Spring Security Authentication
How to configure Spring Security Authorization
How Spring Security Authentication works
How to setup JDBC authentication with Spring Security from scratch
Spring Boot + Spring Security with JPA authentication and MySQL from scratch
Spring Boot + Spring Security + LDAP from scratch
What is JWT authorization really about
What is the structure of a JWT
Spring Boot + Spring Security + JWT from scratch
What is OAuth really all about – OAuth tutorial
OAuth terminologies and flows explained – OAuth tutorial
Implementing login with Facebook and Github from scratch

Spring Framework

Spring Tutorial 01 – Understanding Dependency Injection
Spring Tutorial 02 – Setting Up
Spring Tutorial 03 – Understanding Spring Bean Factory
Spring Tutorial 04 – Writing Code Using the Bean Factory
Spring Tutorial 05 – ApplicationContext and Property Initialization
Spring Tutorial 06 – Using Constructor Injection
Spring Tutorial 07 – Injecting Objects
Spring Tutorial 08 – Inner Beans, Aliases and idref
Spring Tutorial 09 – Initializing Collections
Spring Tutorial 10 – Bean Autowiring
Spring Tutorial 11 – Understanding Bean Scopes
Spring Tutorial 12 – Using ApplicationContextAware
Spring Tutorial 13 – Bean Definition Inheritance
Spring Tutorial 14 – Lifecycle Callbacks
Spring Tutorial 15 – Writing a BeanPostProcessor
Spring Tutorial 16 – Writing a BeanFactoryPostProcessor
Spring Tutorial 17 – Coding To Interfaces
Spring Tutorial 18 – Introduction to Annotations and the Required Annotation
Spring Tutorial 19 – The Autowired Annotation
Spring Tutorial 20 – Some JSR-250 Annotations
Spring Tutorial 21 – Component and Stereotype Annotations
Spring Tutorial 22 – Using MessageSource To Get Text From Property Files
Spring Tutorial 23 – Event Handling in Spring
Spring Tutorial 24 – Introduction to AOP

Spring Boot Quick Start

Spring Boot Quick Start 1 – Introduction
Spring Boot Quick Start 2 – About The Course
Spring Boot Quick Start 3 – What is Spring Boot
Spring Boot Quick Start 4 – Spring and some of its problems
Spring Boot Quick Start 5 – What Spring Boot gives us
Spring Boot Quick Start 6 – Setting Up Development Environment
Spring Boot Quick Start 7 – Maven
Spring Boot Quick Start 8 – Creating a Spring Boot project
Spring Boot Quick Start 9 – Starting a Spring Boot application
Spring Boot Quick Start 10 – Spring Boot startup steps
Spring Boot Quick Start 11 – Adding a REST Controller
Spring Boot Quick Start 12 – Returning Objects From Controller
Spring Boot Quick Start 13 – What’s Happening Here: Bill Of Materials
Spring Boot Quick Start 14 – What’s Happening Here: Embedded Servlet Container
Spring Boot Quick Start 15 – How Spring MVC Works
Spring Boot Quick Start 16 – The REST API we’ll build
Spring Boot Quick Start 17 – Creating a business service
Spring Boot Quick Start 18 – Getting a single resource
Spring Boot Quick Start 19 – Creating a new resource using POST
Spring Boot Quick Start 20 – Implementing Update and Delete
Spring Boot Quick Start 21 – Unit Overview
Spring Boot Quick Start 22 – Using Spring Initializr
Spring Boot Quick Start 23 – Using Spring Boot CLI
Spring Boot Quick Start 24 – Using the STS IDE
Spring Boot Quick Start 25 – Using application properties
Spring Boot Quick Start 26 – What is JPA
Spring Boot Quick Start 27 – Adding Spring Data JPA
Spring Boot Quick Start 28 – Creating a Spring Data JPA Repository
Spring Boot Quick Start 29 – Making Crud Operations with Repository
Spring Boot Quick Start 30 – Adding Course APIs
Spring Boot Quick Start 31 – Adding Entity Relationship and Extending Repository
Spring Boot Quick Start 32 – Packaging and running a Spring Boot app
Spring Boot Quick Start 33 – Spring Boot Actuator
Spring Boot Quick Start 34 – Wrap Up

YouTube: Sarada Herke – Graph Theory

Leave a reply

Graph Theory part-1

Graph Theory: 01. Seven Bridges of Konigsberg
Graph Theory: 02. Definition of a Graph
Graph Theory: 03. Examples of Graphs
Graph Theory: 04. Families of Graphs
Graph Theory: 05. Connected and Regular Graphs
Graph Theory: 06 Sum of Degrees is ALWAYS Twice the Number of Edges
Graph Theory: 07 Adjacency Matrix and Incidence Matrix
Graph Theory: 08-a Basic Problem Set (part 1/2)
Graph Theory: 08-b Basic Problem Set (part 2/2)

Graph Theory part-2

Graph Theory: 09. Graph Isomorphisms
Graph Theory: 10. Isomorphic and Non-Isomorphic Graphs
BONUS: 10-b Graph Theory with Sage
Graph Theory: 11. Neighbourhood and Bipartite Test with Colours
Graph Theory: 12. Spanning and Induced Subgraphs
Graph Theory: 13. Degrees at Least Two Means a Cycle Exists

Graph Theory part-3

Graph Theory: 14a. Basic Graph Theory Problem Set 2
Graph Theory: 14b. Basic Graph Theory Problem Set 2
Graph Theory: 14c. Basic Graph Theory Problem Set 2
Graph Theory: 15.There Exists a 3-Regular Graph of All Even Order at least 4
Graph Theory: 16. Walks Trails and Paths
Graph Theory: 17. Distance Between Vertices and Connected Components

Graph Theory part-4

Graph Theory: 18. Every Walk Contains a Path
Graph Theory: 19. Graph is Bipartite iff No Odd Cycle
Graph Theory: 20. Edge Weighted Shortest Path Problem
Graph Theory: 21. Dijkstra’s Algorithm
Graph Theory: 22. Dijkstra Algorithm Examples

Graph Theory part-5

Graph Theory: 23. Euler Trails and Euler Tours
Graph Theory: 24. Euler Trail iff 0 or 2 Vertices of Odd Degree
Graph Theory: 25. Graph Decompositions
Graph Theory: 26. Cycle Decomposition iff All Vertices Have Even Degre
Graph Theory: 27. Hamiltonian Graphs and Problem Set

Graph Theory part-6

Graph Theory: 28. Hamiltonian Graph Problems
Graph Theory: 29. Lovasz Conjecture on Hamilton Paths
Graph Theory: 30. The 5 Known Vertex-Transitive Non-Hamiltonian Graphs
Graph Theory: 31. Lemma on Hamiltonian Graphs
Graph Theory: 32. Necessary (not sufficient) Condition for Existence of a Hamilton Cycle
Graph Theory: 33. Petersen Graph is Not Hamiltonian

Graph Theory part-7

Graph Theory: 34. Bridge edges
Graph Theory: 35. Bridges in Connected Graphs
Graph Theory: 36. Definition of a Tree
Graph Theory 37. Which Graphs are Trees
Graph Theory: 38. Three ways to Identify Trees
Graph Theory: 39. Types of Trees
Graph Theory: 40. Cayley’s Formula and Prufer Seqences part 1/2
Graph Theory: 41. Cayley’s Formula and Prufer Seqences part 2/2

Graph Theory part-8

Graph Theory: 42. Degree Sequences and Graphical Sequences
Graph Theory: 43. Havel-Hakimi Theorem on Graphical Sequences
Graph Theory: 44. Degree Sequence of a Tree
Graph Theory: 45. Specific Degrees in a Tree
Graph Theory: 46. Relation Between Minimun Degree and Subtrees
Graph Theory: 47. Subgraphs of Regular Graphs
Graph Theory: 48. Complement of a Graph
Graph Theory: 49. Cartesian Product of Graphs

Graph Theory part-9

Graph Theory: 50. Maximum vs Maximal
Graph Theory: 51. Eccentricity, Radius & Diameter
Graph Theory: 52. Radius and Diameter Examples
Graph Theory: 53. Cut-Vertices
Graph Theory: 54. Number of Cut-Vertices
Graph Theory: 55. Bridges and Blocks
Graph Theory: 56. Central Vertices are in a Single Block

Graph Theory part-10

Graph Theory: 57. Planar Graphs
Graph Theory: 58. Euler’s Formula for Plane Graphs
Graph Theory: 59. Maximal Planar Graphs
Graph Theory: 60. Non Planar Graphs
Graph Theory: 61. Characterization of Planar Graphs
Graph Theory: 62. Graph Minors and Wagner’s Theorem
Graph Theory: 63. Petersen Graph is Non-Planar

YouTube: Digital Image Processing by Alan Saberi

Leave a reply

Digital Image procesing

Digital image processing: p000 Welcome and Start Here
Digital image processing: p001 – What is image and video processing (part 1)
Digital image processing: p002 – What is image and video processing (part 2)
Digital image processing: p003 – Course logistics
Digital image processing: p004 – Images are everywhere
Digital image processing: p005- Human visual system
Digital image processing: p006 – Image formation – Sampling Quantization
Digital image processing: p007 The why and how of compression
Digital image processing: p008 – Huffman coding
Digital image processing: p009 JPEGs 8×8 blocks
Digital image processing: p010 – The Discrete Cosine Transform (DCT)
Digital image processing: p011 – Quantization
Digital image processing: p012- JPEG_LS and MPEG
Digital image processing: p013- Bonus Run-length compression
Digital image processing: p014 Introduction to image enhancement
Digital image processing: p015 – Enhancement Histogram modification
Digital image processing: p016 Histogram equalization
Digital image processing: p017- Histogram matching
Digital image processing: p018 Introduction to local neighborhood operations
Digital image processing: P019 Mathematical properties of averaging
Digital image processing: p020 – Non-Local means
Digital image processing: p021 IPOL Demo – Non-Local means
Digital image processing: p022- Median filter
Digital image processing: p023 Demo – Median filter
Digital image processing: p024 – Demo – Unsharp masking
Digital image processing: p025 – Gradients of scalar and vector images
Digital image processing: p026- Concluding remarks
Digital image processing: p027 – What is image restoration
Digital image processing: p028 – Noise types
Digital image processing: p029- Demo – Types of noise
Digital image processing: p030- Demo – Types of noise – Noise and histograms
Digital image processing: p031 – Estimating noise
Digital image processing: p032 – Degradation Function
Digital image processing: p033 – Wiener filtering
Digital image processing: p034 – Demo – Wiener and Box filters
Digital image processing: p035 – Concluding remarks
Digital image processing: p036- Introduction to Segmentation
Digital image processing: p037 – On Edges and Regions
Digital image processing: p038 – Hough Transform with Matlab Demo
Digital image processing: p039 – Line Segment Detector with Demo
Digital image processing: p040- Otsus Segmentation with Demo
Digital image processing: p041 – Congratulations! 😀
Digital image processing: p042 – Interactive Image Segmentation
Digital image processing: p043 Graph Cuts
Digital image processing: p044 – Mumford-Shah
Digital image processing: p045 – Active Contours
Digital image processing: p046 – Behind the Scenes of Adobes Roto Brush
Digital image processing: p047 – End of the Week
Digital image processing: p048- Introduction to PDEs in Image and Video Processing
Digital image processing: p049 – Planar Differential Geometry
Digital image processing: p050 Surface Differential Geometry
Digital image processing: p051- Curve Evolution
Digital image processing: p052 – Level Sets and Curve Evolution
Digital image processing: p053- Calculus of Variations
Digital image processing: p054 – Anisotropic Diffusion
Digital image processing: p055 Active Contours
Digital image processing: p056 Bonus Cool Contrast Enhancement via PDEs
Digital image processing: p057 – Introduction to Image Inpainting
Digital image processing: p058 – Inpainting in Nature
Digital image processing: p059 PDEs and Inpainting
Digital image processing: p060- Inpainting via Calculus of Variations
Digital image processing: p061 Smart Cut and Paste
Digital image processing: p062 – Photoshop Inpainting Healing Brush
Digital image processing: p063- Video Inpainting and Conclusions
Digital image processing: p064 – Introduction to Sparse Modeling – Part 1
Digital image processing: p065 Introduction to Sparse Modeling – Part 2
Digital image processing: p066 – Sparse Modeling – Implementation
Digital image processing: p067- Dictionary Learning
Digital image processing: p068- Sparse Modeling Image Processing Examples
Digital image processing: p069 – A Note on Compressed Sensing
Digital image processing: p070 – GMM and Structured Sparsity
Digital image processing: p071- Bonus Sparse Modeling and Classification – Activity Recognition
Digital image processing: p072- – Introduction to Medical Imaging
Digital image processing: p073- Image Processing and HIV (Part I)
Digital image processing: p074- Image Processing and HIV (Part I)
Digital image processing: p075 – Brain Imaging Diffusion Imaging Deep Brain Stimulation
Digital image processing: p076- – Final course

YouTube: Digital Image Processing by Rich Radke

Leave a reply

Intro to Digital Image Processing (ECSE-4540) Lectures, Spring 2015

DIP Lecture 1: Digital Image Modalities and Processing
DIP Lecture 2: The human visual system, perception, and color
DIP Lecture 3: Image acquisition and sensing
DIP Lecture 4: Histograms and point operations
DIP Lecture 5: Geometric operations
DIP Lecture 6: Spatial filters
DIP Lecture 7: The 2D Discrete Fourier Transform
DIP Lecture 8: Frequency domain filtering; sampling and aliasing
DIP Lecture 9: Unitary image transforms
DIP Lecture 10: Edge detection
DIP Lecture 11: Edge linking and line detection
DIP Lecture 12: Thresholding
DIP Lecture 12a: Image Segmentation
DIP Lecture 12b: Snakes, active contours, and level sets
DIP Lecture 13: Morphological image processing
DIP Lecture 13a: Region description and filtering
DIP Lecture 14: Object and feature detection
DIP Lecture 15: Lossless image coding
DIP Lecture 16: Lossy image compression
DIP Lecture 17: Image restoration and the Wiener filter
DIP Lecture 18: Reconstruction from parallel projections and the Radon transform
DIP Lecture 19: Fan-beam reconstruction
DIP Lecture 20: Dithering and halftoning
DIP Lecture 21: Digital watermarking
DIP Lecture 22: Image blending
DIP Lecture 23: Photomontage and inpainting
DIP Lecture 24: Image retargeting
DIP Lecture 24a: Digital Image Forensics
DIP Lecture 25: Active shape models

Kalman Filter

Leave a reply

KalmanFilter.NET
Kalman Filter For Dummies
What is a Kalman filter?

YouTube

Michel van Biezen

SPECIAL TOPICS 1 – THE KALMAN FILTER

Special Topics – The Kalman Filter (1 of 55) What is a Kalman Filter?
Special Topics – The Kalman Filter (2 of 55) Flowchart of a Simple Example (Single Measured Value)
Special Topics – The Kalman Filter (3 of 55) The Kalman Gain: A Closer Look
Special Topics – The Kalman Filter (4 of 55) The 3 Calculations of the Kalman Filter
Special Topics – The Kalman Filter (5 of 55) A Simple Example of the Kalman Filter
Special Topics – The Kalman Filter (6 of 55) A Simple Example of the Kalman Filter (Continued)
Special Topics – The Kalman Filter (7 of 55) The Multi-Dimension Model 1
Special Topics – The Kalman Filter (8 of 55) The Multi-Dimension Model 2-The State Matrix
Special Topics – The Kalman Filter (9 of 55) The Multi-Dimension Model 3: The State Matrix
Special Topics – The Kalman Filter (10 of 55) 4: The Control Variable Matrix
Special Topics – The Kalman Filter (11 of 55) 5: Find the State Matrix of a Falling Object
Special Topics – The Kalman Filter (12 of 55) 6: Update the State Matrix
Special Topics – The Kalman Filter (13 of 55) 7: State Matrix of Moving Object in 2-D
Special Topics – The Kalman Filter (14 of 55) 8: What is the Control Variable Matrix?
Special Topics – The Kalman Filter (15 of 55) 9: Converting from Previous to Current State 2-D
Special Topics – The Kalman Filter (16 of 55) 10: Converting from Previous to Current State 3-D
Special Topics – The Kalman Filter (17 of 55) 11: Numerical Ex. of Finding the State Matrix 1-D
Special Topics – The Kalman Filter (18 of 55) What is a Covariance Matrix?
Special Topics – The Kalman Filter (19 of 55) What is a Variance-Covariance Matrix?
Special Topics – The Kalman Filter (20 of 55) Example of Covariance Matrix and Standard Deviation
Special Topics – The Kalman Filter (21 of 55) Finding the Covariance Matrix, Numerical Ex. 1
Special Topics – The Kalman Filter (22 of 55) Finding the Covariance Matrix, Numerical Ex. 2
Special Topics – The Kalman Filter (23 of 55) Finding the Covariance Matrix, Numerical Example
Special Topics – The Kalman Filter (24 of 55) Finding the State Covariance Matrix: P=?
Special Topics – The Kalman Filter (25 of 55) Explaining the State Covariance Matrix
Special Topics – The Kalman Filter (26 of 55) Flow Chart of 2-D Kalman Filter – Tracking Airplane
Special Topics – The Kalman Filter (27 of 55) 1. The Predicted State – Tracking Airplane
Special Topics – The Kalman Filter (28 of 55) 2. Initial Process Covariance – Tracking Airplane
Special Topics – The Kalman Filter (29 of 55) 3. Predicted Process Covariance – Tracking Airplane
Special Topics – The Kalman Filter (30 of 55) 4. Calculate the Kalman Gain – Tracking Airplane
Special Topics – The Kalman Filter (31 of 55) 5. The New Observation – Tracking Airplane
Special Topics – The Kalman Filter (32 of 55) 6. Calculate Current State – Tracking Airplane
Special Topics – The Kalman Filter (33 of 55) 7. Update Process Covariance – Tracking Airplane
Special Topics – The Kalman Filter (34 of 55) 8. Current Becomes Previous – Tracking Airplane
Special Topics – The Kalman Filter (35 of 55) 1, 2, 3 of Second Iteration – Tracking Airplane
Special Topics – The Kalman Filter (36 of 55) 4. Kalman Gain Second Iteration – Tracking Airplane
Special Topics – The Kalman Filter (37 of 55) 5, 6 of Second Iteration – Tracking Airplane
Special Topics – The Kalman Filter (38 of 55) 7, 8 of Second Iteration – Tracking Airplane
Special Topics – The Kalman Filter (39 of 55) Part 1 of Third Iteration – Tracking Airplane
Special Topics – The Kalman Filter (40 of 55) Part 2 of Third Iteration – Tracking Airplane
Special Topics – The Kalman Filter (41 of 55) Graphing 1st 3 Iterations (t vs x) – Tracking Airplane
Special Topics – The Kalman Filter (42 of 55) Graphing 1st 3 Iterations (t vs v) – Tracking Airpl***

MATLAB

Understanding Kalman Filters

Understanding Kalman Filters, Part 1: Why Use Kalman Filters?
Understanding Kalman Filters, Part 2: State Observers
Understanding Kalman Filters, Part 3: Optimal State Estimator
Understanding Kalman Filters, Part 4: Optimal State Estimator Algorithm
Understanding Kalman Filters, Part 5: Nonlinear State Estimators
Understanding Kalman Filters, Part 6: How to Use a Kalman Filter in Simulink
Understanding Kalman Filters, Part 7: How to Use an Extended Kalman Filter in Simulink