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Applying CV for Autonomous Vehicles using Python in Hyderabad

This 3 month program from Skill-Lync teaches the student everything there is to know about computer vision. MATLAB will be used as a tool.

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Syllabus

This course is full of best-in-class content by leading faculty and industry experts in the form of videos and projects

Course Overview

  • The program is designed to provide an introductory /Intermediate level explanation of the various concepts in Computer Vision
  • The course is essentially for a sequential approach towards learning computer vision.
  • The course covers the basics of computer vision, understanding the perception of an image/Image sequence (video), working of a camera and applications of computer vision in Industry.
  • The course provides hands-on experience with coding challenges and projects that are relevant in the autonomous vehicle industry.
  • This course is designed to provide an overview and a platform for students to learn the concepts of computer vision and work on collaborative projects.

Course Syllabus in Hyderabad

On a daily basis we talk to companies in the likes of Tata Elxsi and Mahindra to fine tune our curriculum.

Week - 01 Introduction to Computer Vision

  • In this session, we will learn about
    • Introduction to Autonomous Vehicles
    • Introduction to Computer Vision
    • Applications of Computer Vision
    • Course Content - Introduction 
    • Understanding Images 

Week - 02 Image Processing Techniques – I

  • In this session, we will learn about
    • Image Filters 
    • Correlation 
    • Convolution
    • Noise in Images
    • Types of Noise
    • Filters for Noise
    • Image Gradients 
    • Edge Detection Techniques

Week - 03 Image Processing using Edge and Line Detection

  • In this session, we will learn about:
    • Canny Edge Detector 
    • Hough Transformation - Lines
    • Hough Transformation - Circles 
    • Domain Transformation 
    • Understanding Frequency Domain 
    • Spatial to Frequency Domain transformations

Week - 04 Projective and Stereo Geometry

  • In this session, we will learn about
    • Image coordinate systems 
    • Projective Geometry
    • Perspective Projections
    • Multiview Geometry 
    • Stereography and Depth Imaging 
    • Stereo Correspondence

Week - 05 3D Computer Vision

  • In this session, we will learn about:
    • Projective Geometry for 3D
    • Camera calibration methods 
    • Epipolar Geometry
    • Stereovision

Week - 06 Feature Extraction , Neural Networks and Image Classification

  • In this session, we will learn about:
    • Image Classification
    • Dimensionality Reduction
    • Principal Component Analysis
    • Convolutional Neural Networks 
    • Datasets
    • Mobile Net Architecture
    • Image Classification - Performance Metrics

Week - 07 Feature Detectors and Descriptors

  • In this session, we will learn about:
    • Feature Detectors
      • Moravec’s Detector
      • Harris Corner Detector
    • Feature Descriptors
      • SIFT 
      • ORB
    • Feature matching methods

Week - 08 Optical Flow

  • In this session, we will learn about:
    • Optical Flow
    • Horn-Shunck method
    • Lucas Kanade sparse optical flow 
    • Gunnar-Farneback Optical flow 
    • Deep learning based optical flow models 

Week - 09 Object Tracking

  • In this session, we will learn about:
    • Introduction to Object Tracking 
    • Deep SORT
    • Lucas-Kanade-Tomasi(KLT) Tracker 
    • Minimum Of Sum Squared Error (MOSSE) Tracker
    • Mean Shift Tracker  

Week - 10 Image Segmentation

  • In this session, we will learn about:
    • Introduction to Image Segmentation
    • Methods of Segmentation
    • Applications of Segmentation
    • Thresholding based segmentation
    • Otsu’s Thresholding
    • Morphological Operations
    • Connected Components
    • Datasets for image segmentation
    • Deep learning architectures for image segmentation

Week - 11 Object Detection

  • In this session, we will learn about:
    • Introduction to Object Detection
    • Region Proposals
    • Graph cut segmentation
    • Selective search
    • Object Detection Datasets
    • Object Detection Models
    • Tensorflow model zoo
    • Evaluation metrics for object detection models 

Week - 12 3D Object Detection

  • In this session, we will learn about:
    • Introduction to 3D Object Detection
    • Types of 3D Object Detection
    • Stereo Image based Detection
    • Monocular 3D Object Detection

Our courses have been designed by industry experts to help students achieve their dream careers

Industry Projects in Hyderabad

Our projects are designed by experts in the industry to reflect industry standards. By working through our projects, Learners will gain a practical understanding of what they will take on at a larger-scale in the industry. In total, there are 2 Projects that are available in this program.

Implementation of an image classification model using MobileNet architecture

Image Classification is a very important task in deep learning employed in vast areas and has a very high usability and scope. Student will have to understand and implement an image classification model using MobileNet architecture. Also, students should classify the same image with the provided custom dataset

2D Object Detection with tensorFlow

The TensorFlow Object Detection API is an open source framework built on top of TensorFlow that makes it easy to construct, train and deploy object detection models. Student will have to perform 2D Object detection with tensorFlow object detection API. Student will have to submit report on the performance of the model

Our courses have been designed by industry experts to help students achieve their dream careers

Ratings & Reviews by Learners

Skill-Lync has received honest feedback from our learners around the globe.

Google Rating
4.8

All You Need to Know About Applying CV for Autonomous Vehicles Course in Hyderabad

Skill-Lync is one of the best Python institutes in Hyderabad that offers Applying CV for Autonomous Vehicles course. The course will provide you with a deep understanding of CV using MATLAB as the primary tool Computer Vision (CV) is changing how computers process information.

This field of science is receiving prominence because of its use in autonomous vehicle technology. CV concepts in this course specifically focus on autonomous vehicles and detecting objects in real-time. This course is offered by Skill-Lync and is one of the best ways to learn Python and learn about CV and its application in the autonomous vehicles industry.

This course gives you Python training in Hyderabad and trains you in tools and technologies like MATLAB, Keras, Python, OpenCV, TensorFlow, and TensorFlow 2.

FAQs about Applying CV for Autonomous Vehicles using Python course

Why choose the Applying CV for Autonomous Vehicles Course with Skill-Lync at Hyderabad?

The Skill-Lync's Applying CV for Autonomous Vehicles course and Python training in Hyderabad teach you key technologies like Python, MATLAB, TensorFlow and OpenCV. All these tools are popular tools used by top OEMs and learning these could enhance your employability.

What are the prerequisites for taking the Applying CV for Autonomous Vehicles course in Hyderabad?

There are no prerequisites for pursuing the Applying CV for Autonomous Vehicles course. If you are interested in CV technology and its application in autonomous vehicle development, you can opt for this course as it is one of the best online Python courses. 

What is the program fee of Skill-Lync's Applying CV for Autonomous Vehicles course in Hyderabad?

Skill-Lync offers the Python course with flexible fee options and is available in three plans – Basic, Pro, and Premium. The Basic plan is one of the cheapest Python courses in Hyderabad at INR 7,000 per month for three months. You get access for two months after completion.

The Pro and Premium plan costs INR 10,000 and INR 15,000 per month, respectively, for three months. While the Pro plan gives you access for another four months after completing the course, you get lifetime access with the Premium plan.

What are the benefits of pursuing Applying CV for Autonomous Vehicles course at Skill-Lync in Hyderabad?

Applying CV for Autonomous Vehicles course at Skill-Lync in Hyderabad teaches skills like image processing, Python scripting, optical flow of images on a video, and Driving Scenario Design.

What are your career prospects after completing the Applying CV for Autonomous Vehicles course at Skill-Lync in Hyderabad?  

Skill-Lync is one of the Python training institutes in Hyderabad that improves your career prospects. Some jobs available in this field are – Autonomous Driving Machine Learning Engineer, Automotive Solutions Platform Engineer, Robotic Function Developer, etc.

What is the expected salary range after completing the Applying CV for Autonomous Vehicles course at Skill-Lync in Hyderabad?

Autonomous engineers with Python online course certification and knowledge of CV can earn between 4 lakh rupees and 17 lakh rupees. However, your pay package may vary and it primarily depends on your expertise and experience.

Flexible Pricing

Talk to our career counsellors to get flexible payment options.

Premium

INR 40,000

Inclusive of all charges


Become job ready with our comprehensive industry focused curriculum for freshers & early career professionals

  • 1 Year Accessto Skill-Lync’s Learning Management System (LMS)

  • Personalized Pageto showcase Projects & Certifications

  • Live Individual & Group Sessionsto resolve queries, Discuss Progress and Study Plans.

  • Personalized & Hands-OnSupport over Mail, Telephone for Query Resolution & Overall Learner Progress.

  • Job-Oriented Industry Relevant Curriculumavailable at your fingertips curated by Global Industry Experts along with Live Sessions.

Instructors profiles

Our courses are designed by leading academicians and experienced industry professionals.

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1 industry expert

Our instructors are industry experts along with a passion to teach.

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5 years in the experience range

Instructors with 5 years extensive industry experience.

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Areas of expertise

  • Autonomous Vehicle Controls

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