Why this course?

Description

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, artificial intelligence, deep learning etc...Other than learning, this program also provides an industrial exposure of working in these software’s and packages with its relevant application.

Technologies and Tools Covered 

• Python
• Open CV
• Keras
• Tensorflow

 

LEARNING PATH

 1. Python & OpenCV programming

Introduction to the Concept of python and OpenCV will be dealt with. Simple programs shall be done by the participants. This shall serve as the first step into the entry to the advanced concepts implementation using python

 

 

2. Machine Learning Algorithms 

Machine learning brings together computer science and statistics to harness that predictive power. It’s a must-have skill for all aspiring data analysts and data scientists, or anyone else who wants to wrestle all that raw data into refined trends and predictions.

 

DAY1: Introduction to computer vision and its application

DAY2: Read, write and color conversion of images

DAY3: Apply smoothing techniques for images

DAY4: Detecting edges from images 

DAY5: Purpose of morphology techniques

DAY6: Different thresholding techiques

DAY7: Contour Detection Technique

DAY8: How to segment an image using K-Means?

DAY9: Apply color masking to different images

DAY10: What is otsu thresholding?

DAY11: Inserting shapes and texts to images

DAY12: How to play video In reverse mode?

DAY13: Optical character recognition

DAY14: Histogram equalization using opencv

DAY15: Multiple color detection using HSV

DAY16: Detection of lines using hough lines

DAY17: Detection of multiple shapes using edge detection

DAY18: How to blend images using image pyramids

DAY19: Multiple filters used in image processing

DAY20: Background subtraction using Threshold

DAY21: Implementation of template matching

DAY22: Working with Scalar Invariant Feature Transform(SIFT)

DAY23: Working with the PILLOW package

DAY24: Face counting system using haar cascade

DAY25: Age and gender detection

DAY26: Hand gesture detection

DAY27: Image classification using KNN

DAY28: Cortoonify  an image using OpenCV

DAY29: Barcode and QR-code recognition

DAY30: Sudoku solver using image processing

 

Practical Assignments

Assignment 1: Image Transformations

Assignment 2: HSV Conversion based color detection

Assignment 3: Face detection

 

Training Methodology

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.