Industrial Program

Computer Vision and Image Processing

Transform Visual Data into Insights with Advanced Computer Vision Techniques.

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MODE
Online/ e-LMS
TYPE
Self Paced
LEVEL
Advanced
DURATION
12 Weeks

About

This course is designed to provide a comprehensive understanding of computer vision and image processing techniques and applications. Participants will explore the foundational principles of computer vision, including image classification, object detection, and image segmentation. The course will delve into advanced topics such as facial recognition and the use of deep learning in computer vision. By the end of the course, participants will be proficient in using key computer vision

Program Objectives

  • Understand and apply foundational computer vision concepts and techniques.
  • Perform image preprocessing, classification, and segmentation.
  • Implement object detection algorithms like YOLO and Faster R-CNN.
  • Develop and train convolutional neural networks (CNNs) for image analysis.
  • Utilize transfer learning for efficient model development.
  • Implement facial recognition systems, including face detection and alignment.
  • Gain proficiency in advanced computer vision tasks using deep learning frameworks.
  • Apply computer vision techniques to real-world applications and projects.
  • Enhance coding skills in Python and use libraries such as OpenCV, TensorFlow, and Keras.

Program Structure

Introduction to Computer Vision:

  • Overview of Computer Vision and its Applications.
  • Key Concepts and Terminologies in Computer Vision.
  • Image Processing Basics.

Image Classification:

  • Introduction to Image Classification.
  • Convolutional Neural Networks (CNNs).
  • Training CNNs for Image Classification.
  • Transfer Learning for Image Classification.

Object Detection:

  • Basics of Object Detection.
  • YOLO (You Only Look Once) Algorithm.
  • Faster R-CNN (Region-Based Convolutional Neural Networks).
  • Implementing Object Detection Models.

Image Segmentation:

  • Introduction to Image Segmentation.
  • Semantic Segmentation.
  • Instance Segmentation.
  • Using U-Net for Image Segmentation.

Facial Recognition:

  • Understanding Facial Recognition.
  • Face Detection and Alignment.
  • Face Embeddings and Recognition.
  • Implementing Facial Recognition Systems.

Advanced Computer Vision with Deep Learning:

  • Deep Learning Architectures for Computer Vision.
  • Implementing Advanced Models with TensorFlow and Keras.
  • Real-World Applications of Computer Vision.

Participant’s Eligibility

  • Senior undergraduates and graduate students in Computer Science and related fields.
  • Professionals in IT, data science, and software development looking to enhance their computer vision skills.

Program Outcomes

  • Gain a solid understanding of computer vision and image processing principles.
  • Develop proficiency in image classification, object detection, and image segmentation.
  • Implement facial recognition systems and advanced computer vision models.
  • Master the use of key computer vision libraries such as OpenCV, TensorFlow, and Keras.
  • Apply computer vision concepts to real-world projects and scenarios.
  • Enhance Python programming skills for advanced computer vision tasks.
  • Complete practical coding exercises and projects demonstrating computer vision expertise.
  • Earn a certificate of completion recognized by industry leaders.


Fee Structure

Standard Fee:           INR 14,998           USD 258

Discounted Fee:       INR 7499             USD 129

Batches

Spring
Summer

Autumn
Winter

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Certificate

Program Assessment

Certification to this program will be based on the evaluation of following assignment (s)/ examinations:

Exam Weightage
Mid Term Assignments 20 %
Final Online Exam 30 %
Project Report Submission (Includes Mandatory Paper Publication) 50 %

To study the printed/online course material, submit and clear, the mid term assignments, project work/research study (in completion of project work/research study, a final report must be submitted) and the online examination, you are allotted a 1-month period. You will be awarded a certificate, only after successful completion/ and clearance of all the aforesaid assignment(s) and examinations.

Program Deliverables

  • Access to e-LMS
  • Real Time Project for Dissertation
  • Project Guidance
  • Paper Publication Opportunity
  • Self Assessment
  • Final Examination
  • e-Certification
  • e-Marksheet

Future Career Prospects

  • Computer Vision Engineer: Design and implement computer vision algorithms and applications.
  • Data Scientist: Analyze visual data to extract insights and support data-driven decision-making.
  • AI Research Scientist: Conduct research to advance the field of computer vision and develop new techniques.
  • Machine Learning Engineer: Develop and optimize machine learning models for image and video analysis.
  • Software Developer: Integrate computer vision capabilities into software applications.
  • Robotics Engineer: Apply computer vision techniques to robotics and automation systems.

Enter the Hall of Fame!

Take your research to the next level!

Publication Opportunity
Potentially earn a place in our coveted Hall of Fame.

Centre of Excellence
Join the esteemed Centre of Excellence.

Networking and Learning
Network with industry leaders, access ongoing learning opportunities.

Hall of Fame
Get your groundbreaking work considered for publication in a prestigious Open Access Journal (worth ₹20,000/USD 1,000).

Achieve excellence and solidify your reputation among the elite!


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