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Computer Vision and Image Processing
Transform Visual Data into Insights with Advanced Computer Vision Techniques.
Enroll now for early access of e-LMS
Online/ e-LMS
Self Paced
Advanced
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
We are excited to announce that we now accept payments in over 20 global currencies, in addition to USD. Check out our list to see if your preferred currency is supported. Enjoy the convenience and flexibility of paying in your local currency!
List of CurrenciesBatches
Live
Certificate
Program Assessment
Certification to this program will be based on the evaluation of following assignment (s)/ examinations:
| Exam | Weightage |
|---|---|
| Mid Term Assignments | 50 % |
| 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!
Achieve excellence and solidify your reputation among the elite!
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Recent Feedbacks In Other Workshops
The course was more theoretical than practical.
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