Certification in Computer Vision
What you'll learn
- You will learn the key concepts in Computer Vision, starting with an introduction to computer vision and its foundational principles
- The course covers image representation and feature engineering, which are crucial for understanding and manipulating visual data.
- You will delve into image classification methods, which are essential for categorizing and organizing images.
- You will learn the key concepts in Computer Vision, starting with an introduction to computer vision and its foundational principles.
- The course covers image representation and feature engineering, which are crucial for understanding and manipulating visual data
- You will delve into image classification methods, which are essential for categorizing and organizing images.
- The course includes advanced topics and practical applications in computer vision, such as object detection and image segmentation
- Learn about image preprocessing and analysis, including their roles in understanding and manipulating the structure of images.
- Learn about image recognition and generation, including techniques for identifying objects within images and creating coherent & contextually relevant content
- You will explore advanced topics in computer vision, which delve into cutting-edge research and applications in the field.
- Learn about computer vision applications and future trends, focusing on how computer vision is utilized in various industries
- This training will be useful if your job involves applying computer vision techniques in practical scenarios
- Discover how to gain insights into the evolving landscape of computer vision and stay updated with the latest advancements and trends.
Requirements
- You should have an interest in computer vision and its applications.
- An interest in image representation and feature engineering. Image classification. Object Detection and Image Segmentation. Image Preprocessing and Analysis. Image Recognition and Generation. Image Captioning and Visual Question Answering. Advanced Topics in Computer Vision. Computer Vision Applications and Future Trends. Capstone Project in Computer Vision.
- Be interested in gaining knowledge of image recognition and generation, object detection and image segmentation, image captioning and visual question answering, and advanced topics in computer vision.
- Have an interest in understanding computer vision applications and future trends, advanced topics in computer vision, and the capstone project in computer vision.
Description
Description
Take the next step in your career as Computer Vision professionals! Whether you’re an up-and-coming computer vision engineer, an experienced image analyst, aspiring machine learning specialist in computer vision, or budding AI researcher in visual technology, this course is an opportunity to sharpen your image processing and analytical capabilities, increase your efficiency for professional growth, and make a positive and lasting impact in the field of Computer Vision.
With this course as your guide, you learn how to:
● All the fundamental functions and skills required for Computer Vision.
● Transform knowledge of Computer Vision applications and techniques, image representation and feature engineering, image analysis and preprocessing, object detection and image segmentation.
● Get access to recommended templates and formats for details related to Computer Vision applications and techniques.
● Learn from informative case studies, gaining insights into Computer Vision applications and techniques for various scenarios. Understand how the International Monetary Fund, monetary policy, and fiscal policy impact advancements in Computer Vision, with practical forms and frameworks.
● Learn from informative case studies, gaining insights into Computer Vision applications and techniques for various scenarios. Understand how the International Monetary Fund, monetary policy, and fiscal policy impact advancements in Computer Vision, with practical forms and frameworks.
The Frameworks of the Course
Engaging video lectures, case studies, assessments, downloadable resources, and interactive exercises. This course is designed to explore the field of Computer Vision, covering various chapters and units. You'll delve into image representation, feature engineering, image classification, object detection, image segmentation, image preprocessing, image analysis, image recognition, image generation, image captioning, visual question answering, advanced Computer Vision topics, and future trends.
The socio-cultural environment module using Computer Vision techniques delves into sentiment analysis and opinion mining, image captioning and visual question answering, and object detection and image segmentation in the context of India's socio-cultural landscape. It also applies Computer Vision to explore image preprocessing and analysis, image recognition, object detection, image segmentation, and advanced topics in Computer Vision. You'll gain insight into Computer Vision-driven analysis of sentiment analysis and opinion mining, image captioning and visual question answering, and object detection and image segmentation. Furthermore, the content discusses Computer Vision-based insights into Computer Vision applications and future trends, along with a capstone project in Computer Vision.
The course includes multiple global Computer Vision projects, resources like formats, templates, worksheets, reading materials, quizzes, self-assessment, film study, and assignments to nurture and upgrade your global Computer Vision knowledge in detail.
Course Content:
Part 1
Introduction and Study Plan
● Introduction and know your Instructor
● Study Plan and Structure of the Course
1. Introduction to Computer Vision
1.1.1 Overview of Computer Vision
1.1.2 Key Components of Computer Vision
1.2.3 Pattern Recognition
1.1.4 Technique and Algorithms
1.1.5 Challenges in Computer Vision
1.1.6 Basic of Image Processing with Python
1.1.7 Key Libraries for image processing in Python
1.1.8 Basic Image Operation
1.1.8 Continuation of Basic Image Operation
1.1.8 Continuation of Basic Image Operation
2. Image Representation and Feature Extraction
2.1.1 Image Representation and Feature Extraction
2.1.1 Continuation of image Representation and Feature Extraction
2.1.2 Corner Detection
2.1.3 HOG(Histogram of Oriented Gradients)
3. Image Segmentation
3.1.1 Image Segmentation
3.1.2 Types of image Segmentation
3.1.3 Technique and Implementations
3.1.4 K-Means Clustering
3.1.5 Watershed Algorithm
3.1.6 Summary
4. Object Detection
4.1.1 Object Detection
4.1.2 Key Concepts in Object Detection
4.1.3 Implementing Object Detection with Pre trained Models
4.1.4 YOLO(You only Look Once)
4.1.5 Faster R-CNN with TensorFlow
4.1.6 Summary
5. Image Classification
5.1.1 Image Classification
5.1.2 Key Components in image Classification
5.1.3 Implementing image Classification
5.1.4 Deep learning Methods
6. Image Recognition and Scene Understanding
6.1.1 Image Recognition and Scene Understanding
6.1.2 Key Concepts
6.1.3 Implementations
6.1.4 Scene Understanding with Semantic Segmentation
6.1.5 Instance Segmentation with Mask R-CNN
6.1.6 Scene Classification with RNN and CNN
6.1.6 Continuation of Scene Classification with RNN and CNN
7. Object Tracking
7.1.1 Object Tracking
7.1.2 Key Concepts
7.1.3 KLT Tracker with OpenCV
7.1.4 Deep SORT with YAOLOv4 for Detection
8. Image Generation and Image-to-Image Translation
8.1.1 Image Generation and image to Image Translation
8.1.2 key concepts
8.1.3 Implementations
8.1.4 Image to Image Translation with Pix2Pix
8.1.5 Cycle gan for Unpaired Image to Image Translation
8.1.5 Continuation of Cycle gan for Unpaired Image to Image Translation
9. Advanced Topics in Computer Vision
9.1.1 Advanced Topics in Computer Vision
9.1.1 Continuation of Advanced Topics in Computer Vision
9.1.1 Continuation of Advanced Topics in Computer Vision
10. Computer Vision Applications and Future Trends
10.1.1 Computer Vision Applications and Future Trends
10.1.2 Application
10.1.3 Future Trends
10.1.3 Continuation of Future Trends
11. Capstone Project
11.1.1 Capstone Project
11.1.2 Project Title Real-world Object Detection and Classification System
11.1.3 Project Tasks
11.1.3 Continuation of project Tasks
11.1.4 Project Deliverables
11.1.5 Project Evaluation
11.1.6 Conclusion
Part 3
Assignments
Who this course is for:
- Professionals with a deep understanding of computer vision applications, advanced topics in computer vision, and a desire to excel in the field of visual processing and analysis.
- New professionals aiming for success in computer vision applications and the economic environment of visual technology in business.
- Existing executive board directors, managing directors who are seeking greater engagement and innovation from their teams and organizations in the realm of Computer Vision technology.
Instructor
- 4.2 Instructor Rating
- 10,887 Reviews
- 140,004 Students
- 144 Courses
Achievements
"Globally 125,000 plus Students + 121 Countries + 50 plus Languages + 200 plus Courses designed on Business, General Management, HR, Process Management, Quality Management, Project Management, MBA Essentials, Office Productivity and Leadership"
Bestseller, Hot & New and Highest Rated Tag in Udemy, inclusion in Udemy Business.
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