Certification in Computer Vision

Published 7/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Language: English | Duration: 6h 40m | Size: 2.18 GB

Learn Computer Vision for image representation, feature engineering, image preprocessing, analysis, application & trend

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
DescriptionTake 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 CourseEngaging 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 1Introduction and Study Plan● Introduction and know your Instructor● Study Plan and Structure of the Course1. Introduction to Computer Vision1.1.1 Overview of Computer Vision1.1.2 Key Components of Computer Vision1.2.3 Pattern Recognition1.1.4 Technique and Algorithms1.1.5 Challenges in Computer Vision1.1.6 Basic of Image Processing with Python1.1.7 Key Libraries for image processing in Python1.1.8 Basic Image Operation1.1.8 Continuation of Basic Image Operation1.1.8 Continuation of Basic Image Operation2. Image Representation and Feature Extraction2.1.1 Image Representation and Feature Extraction2.1.1 Continuation of image Representation and Feature Extraction2.1.2 Corner Detection2.1.3 HOG(Histogram of Oriented Gradients)3. Image Segmentation3.1.1 Image Segmentation3.1.2 Types of image Segmentation3.1.3 Technique and Implementations3.1.4 K-Means Clustering3.1.5 Watershed Algorithm3.1.6 Summary4. Object Detection4.1.1 Object Detection4.1.2 Key Concepts in Object Detection4.1.3 Implementing Object Detection with Pre trained Models4.1.4 YOLO(You only Look Once)4.1.5 Faster R-CNN with TensorFlow4.1.6 Summary5. Image Classification5.1.1 Image Classification5.1.2 Key Components in image Classification5.1.3 Implementing image Classification5.1.4 Deep learning Methods6. Image Recognition and Scene Understanding6.1.1 Image Recognition and Scene Understanding6.1.2 Key Concepts6.1.3 Implementations6.1.4 Scene Understanding with Semantic Segmentation6.1.5 Instance Segmentation with Mask R-CNN6.1.6 Scene Classification with RNN and CNN6.1.6 Continuation of Scene Classification with RNN and CNN7. Object Tracking7.1.1 Object Tracking7.1.2 Key Concepts7.1.3 KLT Tracker with OpenCV7.1.4 Deep SORT with YAOLOv4 for Detection8. Image Generation and Image-to-Image Translation8.1.1 Image Generation and image to Image Translation8.1.2 key concepts8.1.3 Implementations8.1.4 Image to Image Translation with Pix2Pix8.1.5 Cycle gan for Unpaired Image to Image Translation8.1.5 Continuation of Cycle gan for Unpaired Image to Image Translation9. Advanced Topics in Computer Vision9.1.1 Advanced Topics in Computer Vision9.1.1 Continuation of Advanced Topics in Computer Vision9.1.1 Continuation of Advanced Topics in Computer Vision10. Computer Vision Applications and Future Trends10.1.1 Computer Vision Applications and Future Trends10.1.2 Application10.1.3 Future Trends10.1.3 Continuation of Future Trends11. Capstone Project11.1.1 Capstone Project11.1.2 Project Title Real-world Object Detection and Classification System11.1.3 Project Tasks11.1.3 Continuation of project Tasks11.1.4 Project Deliverables11.1.5 Project Evaluation11.1.6 ConclusionPart 3Assignments

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.

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