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Description Vision therapy can help certain conditions other than nearsightedness, farsightedness, and astigmatism. This Natural Vision Improvement with Eye Gymnastics designed for you to help you work towards improving the overall health of your eyes in a completely natural way. The goal is to develop, heal, or improve how you see.  You will explore methods that will relax and improve your vision (day and night!). You will learn how to read more easily, focus in the distance, expand peripheral vision and apply the techniques to sports and ergonomics for computers and handheld devices. You will learn two simple eye relaxation techniques that may help to defuse stress around the face, neck, shoulders, and body. The course also includes meditation to see from the core and mind, ideas for customizing the workspace for maximum visual enhancement and yoga sets. Assessment and Certification: This course does not involve any assessment. Students can order their course completion Certificate at an additional cost of £39 for hard copy and in PDF format at £24. Who is this Course for? Natural Vision Improvement with Eye Gymnastics is certified by CPD Qualifications Standards and CiQ. This makes it perfect for anyone trying to learn potential professional skills. As there is no experience and qualification required for this course, it is available for all students from any academic background. Requirements Our Natural Vision Improvement with Eye Gymnastics is fully compatible with any kind of device. Whether you are using Windows computer, Mac, smartphones or tablets, you will get the same experience while learning. Besides that, you will be able to access the course with any kind of internet connection from anywhere at any time without any kind of limitation. Career Path After completing this course you will be able to build up accurate knowledge and skills with proper confidence to enrich yourself and brighten up your career in the relevant job market. Introduction Introduction 00:01:00 Improve Your Vision Naturally 00:01:00 What is 'Eye Gymnastics'? 00:02:00 A Few Words Before We Begin 00:01:00 Eye Relaxation Technique Eye Relaxation Technique 1 Coverpage 00:01:00 Eye Relaxation Technique 1 00:01:00 Eye Relaxation Technique 1 - with Music (Approx 5 Minutes) 00:05:00 Eye Relaxation Technique 2 Coverpage 00:01:00 Eye Relaxation Technique 2 00:01:00 Eye Relaxation Technique 2 - with Music (Approx 5 Minutes) 00:05:00 Eye Gymnastics Exercise Eye Gymnastics Exercises Coverpage 00:02:00 Eye Gymnastics Exercise 1 00:02:00 Eye Gymnastics Exercise 2 00:02:00 Eye Gymnastics Exercise 3 00:02:00 Eye Gymnastics Exercise 4 00:02:00 Eye Gymnastics Exercise 5 00:02:00 Eye Gymnastics Exercie 6 00:02:00 Eye Gymnastics Exercise 7 00:02:00 Eye Gymnastics Exercise 8 00:02:00 Eye Gymnastics Exercise 9 00:02:00 Eye Gymnastics Exercise 10 00:02:00 Eye Gymnastics Exercise 11 00:02:00 Eye Gymnastics Exercise 12 00:02:00 Order Your Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

The comprehensive Computer Vision: C++ and OpenCV with GPU support has been designed by industry experts to provide learners with everything they need to enhance their skills and knowledge in their chosen area of study. Enrol on the Computer Vision: C++ and OpenCV with GPU support today, and learn from the very best the industry has to offer! This best selling Computer Vision: C++ and OpenCV with GPU support has been developed by industry professionals and has already been completed by hundreds of satisfied students. This in-depth Computer Vision: C++ and OpenCV with GPU support is suitable for anyone who wants to build their professional skill set and improve their expert knowledge. The Computer Vision: C++ and OpenCV with GPU support is CPD-accredited, so you can be confident you're completing a quality training course will boost your CV and enhance your career potential. The Computer Vision: C++ and OpenCV with GPU support is made up of several information-packed modules which break down each topic into bite-sized chunks to ensure you understand and retain everything you learn. After successfully completing the Computer Vision: C++ and OpenCV with GPU support, you will be awarded a certificate of completion as proof of your new skills. If you are looking to pursue a new career and want to build your professional skills to excel in your chosen field, the certificate of completion from the Computer Vision: C++ and OpenCV with GPU support will help you stand out from the crowd. You can also validate your certification on our website. We know that you are busy and that time is precious, so we have designed the Computer Vision: C++ and OpenCV with GPU support to be completed at your own pace, whether that's part-time or full-time. Get full course access upon registration and access the course materials from anywhere in the world, at any time, from any internet-enabled device.  Our experienced tutors are here to support you through the entire learning process and answer any queries you may have via email.

The Computer Vision course with C++ and OpenCV with GPU support provides an introduction to computer vision and its applications using C++ and OpenCV with GPU acceleration. Students will learn about setting up the necessary environments, basic examples, background segmentation, object detection with OpenCV's ML module using C++ and CUDA, and optical flow. Learning Outcomes: Set up the required environments for C++ and OpenCV with GPU support. Understand the fundamentals of computer vision and its applications. Implement background segmentation techniques to extract relevant objects from the environment. Use OpenCV's ML module with C++ and CUDA to perform object detection efficiently. Apply optical flow algorithms to track object movements and analyze motion patterns. Why buy this Computer Vision: C++ and OpenCV with GPU support? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Computer Vision: C++ and OpenCV with GPU support there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this course for? This Computer Vision: C++ and OpenCV with GPU support course is ideal for Students Recent graduates Job Seekers Anyone interested in this topic People already working in the relevant fields and want to polish their knowledge and skill. Prerequisites This Computer Vision: C++ and OpenCV with GPU support does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Computer Vision: C++ and OpenCV with GPU support was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path As this course comes with multiple courses included as bonus, you will be able to pursue multiple occupations. This Computer Vision: C++ and OpenCV with GPU support is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Unit 01: Set up Necesssary Environments Module 01: Driver installation 00:06:00 Module 02: Cuda toolkit installation 00:01:00 Module 03: Compile OpenCV from source with CUDA support part-1 00:06:00 Module 04: Compile OpenCV from source with CUDA support part-2 00:05:00 Module 05: Python environment for flownet2-pytorch 00:09:00 Unit 02: Introduction with a few basic examples! Module 01: Read camera & files in a folder (C++) 00:11:00 Module 02: Edge detection (C++) 00:08:00 Module 03: Color transformations (C++) 00:07:00 Module 04: Using a trackbar (C++) 00:06:00 Module 05: Image filtering with CUDA (Introduction to using OpenCV GPU methods on C++) 00:13:00 Unit 03: Background segmentation Module 01: Background segmentation with MOG (C++) 00:04:00 Module 02: MOG and MOG2 cuda implementation (C++ - CUDA) 00:03:00 Module 03: Special app: Track class 00:06:00 Module 04: Special app: Track bgseg Foreground objects 00:08:00 Unit 04: Object detection with openCV ML module (C++ CUDA) Module 01: A simple application to prepare dataset for object detection (C++) 00:08:00 Module 02: Train model with openCV ML module (C++ and CUDA) 00:13:00 Module 03: Object detection with openCV ML module (C++ CUDA) 00:06:00 Unit 05: Optical Flow Module 01: Optical flow with Farneback (C++) 00:08:00 Module 02: Optical flow with Farneback (C++ CUDA) 00:06:00 Module 03: Optical flow with Nvidia optical flow SDK (C++ CUDA) 00:05:00 Module 04: Optical flow with Nvidia Flownet2 (Python) 00:05:00 Module 05: Performance Comparison 00:07:00 Additional Resource Resources - Computer Vision: C++ and OpenCV with GPU support 00:00:00 Assignment Assignment - Computer Vision: C++ and OpenCV with GPU support 00:00:00

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Computer vision (CV), a subfield of computer science, focuses on replicating the complex functionalities of the human visual system. This course provides a comprehensive understanding of Computer Vision from the beginning using Python and helps you in becoming an expert.

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Duration 3 Days 18 CPD hours This course is intended for This course is geared for attendees with Intermediate IT skills who wish to learn Computer Vision with tensor flow 2 Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Working in a hands-on learning environment, led by our Computer Vision expert instructor, students will learn about and explore how to Build, train, and serve your own deep neural networks with TensorFlow 2 and Keras Apply modern solutions to a wide range of applications such as object detection and video analysis Run your models on mobile devices and web pages and improve their performance. Create your own neural networks from scratch Classify images with modern architectures including Inception and ResNet Detect and segment objects in images with YOLO, Mask R-CNN, and U-Net Tackle problems faced when developing self-driving cars and facial emotion recognition systems Boost your application's performance with transfer learning, GANs, and domain adaptation Use recurrent neural networks (RNNs) for video analysis Optimize and deploy your networks on mobile devices and in the browser Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. Hands-On Computervision with TensorFlow 2 is a hands-on course that thoroughly explores TensorFlow 2, the brandnew version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. This course begins with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the course demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative dversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts Computer Vision and Neural Networks Computer Vision and Neural Networks Technical requirements Computer vision in the wild A brief history of computer vision Getting started with neural networks TensorFlow Basics and Training a Model TensorFlow Basics and Training a Model Technical requirements Getting started with TensorFlow 2 and Keras TensorFlow 2 and Keras in detail The TensorFlow ecosystem Modern Neural Networks Modern Neural Networks Technical requirements Discovering convolutional neural networks Refining the training process Influential Classification Tools Influential Classification Tools Technical requirements Understanding advanced CNN architectures Leveraging transfer learning Object Detection Models Object Detection Models Technical requirements Introducing object detection A fast object detection algorithm YOLO Faster R-CNN ? a powerful object detection model Enhancing and Segmenting Images Enhancing and Segmenting Images Technical requirements Transforming images with encoders-decoders Understanding semantic segmentation Training on Complex and Scarce Datasets Training on Complex and Scarce Datasets Technical requirements Efficient data serving How to deal with data scarcity Video and Recurrent Neural Networks Video and Recurrent Neural Networks Technical requirements Introducing RNNs Classifying videos Optimizing Models and Deploying on Mobile Devices Optimizing Models and Deploying on Mobile Devices Technical requirements Optimizing computational and disk footprints On-device machine learning Example app ? recognizing facial expressions

Overview This comprehensive course on Computer Vision: C++ and OpenCV with GPU support will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Computer Vision: C++ and OpenCV with GPU support comes with accredited certification, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Computer Vision: C++ and OpenCV with GPU support. It is available to all students, of all academic backgrounds. Requirements Our Computer Vision: C++ and OpenCV with GPU support is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 5 sections • 22 lectures • 02:31:00 total length •Module 01: Driver installation: 00:06:00 •Module 02: Cuda toolkit installation: 00:01:00 •Module 03: Compile OpenCV from source with CUDA support part-1: 00:06:00 •Module 04: Compile OpenCV from source with CUDA support part-2: 00:05:00 •Module 05: Python environment for flownet2-pytorch: 00:09:00 •Module 01: Read camera & files in a folder (C++): 00:11:00 •Module 02: Edge detection (C++): 00:08:00 •Module 03: Color transformations (C++): 00:07:00 •Module 04: Using a trackbar (C++): 00:06:00 •Module 05: Image filtering with CUDA (Introduction to using OpenCV GPU methods on C++): 00:13:00 •Module 01: Background segmentation with MOG (C++): 00:04:00 •Module 02: MOG and MOG2 cuda implementation (C++ - CUDA): 00:03:00 •Module 03: Special app: Track class: 00:06:00 •Module 04: Special app: Track bgseg Foreground objects: 00:08:00 •Module 01: A simple application to prepare dataset for object detection (C++): 00:08:00 •Module 02: Train model with openCV ML module (C++ and CUDA): 00:13:00 •Module 03: Object detection with openCV ML module (C++ CUDA): 00:06:00 •Module 01: Optical flow with Farneback (C++): 00:08:00 •Module 02: Optical flow with Farneback (C++ CUDA): 00:06:00 •Module 03: Optical flow with Nvidia optical flow SDK (C++ CUDA): 00:05:00 •Module 04: Optical flow with Nvidia Flownet2 (Python): 00:05:00 •Module 05: Performance Comparison: 00:07:00

Eye exercises help you strengthen your visual fitness. People with fit eyes react smarter in case of emergency. While driving, their chances to escape an accident are greater than people lacking visual fitness. Since electronic devices surround our daily life, we spend a long time staring at the screen leading to so many visual troubles. Hence, this course will help you to develop your visual quality and save your precious eyes from going blind or low-sighted. A simple eye exercise can help you get over with the severity and handle the daily pressure on your eyes. This course fulfills the purpose of coaching you the eye exercises to improve your vision. What you'll learn Apply 2 Simple Eye Relaxation Techniques that may help to defuse stress around the Face, Neck, Shoulders, and Body Complete a Set of 12 Simple Eye Gymnastics Exercises Daily that may help to Improve Vision in a Completely Natural way Use the recipes provided in the FREE ebook 'Nutrition for Eye Health' to help ensure Optimum Vision Requirements No previous experience is required as full details will be provided throughout the course It is suggested that a person undertaking this eye gymnastics course should gradually decrease the amount of time spent wearing corrective lenses during the day and that fundamental eye gymnastics be performed without wearing glasses or contacts to lessen dependency on mechanical aids Who this course is for: This course has been created for students of 'All Levels' Introduction Introduction FREE 00:01:00 Improve Your Vision Naturally 00:01:00 What is 'Eye Gymnastics'? 00:02:00 A Few Words Before We Begin 00:01:00 Eye Relaxation Techniques Eye Relaxation Technique 1 Coverpage 00:01:00 Eye Relaxation Technique 1 00:01:00 Eye Relaxation Technique 2 - with Music (Approx 5 Minutes) 00:05:00 Eye Relaxation Technique 2 Coverpage 00:01:00 Eye Relaxation Technique 2 00:01:00 Eye Relaxation Technique 2 - with Music (Approx 5 Minutes) 00:05:00 Eye Gymnastics Exercises Eye Gymnastics Exercises Coverpage 00:02:00 Eye Gymnastics Exercise 1 00:02:00 Eye Gymnastics Exercise 2 00:02:00 Eye Gymnastics Exercise 3 00:02:00 Eye Gymnastics Exercise 4 00:02:00 Eye Gymnastics Exercise 5 00:02:00 Eye Gymnastics Exercise 6 00:02:00 Eye Gymnastics Exercise 7 00:02:00 Eye Gymnastics Exercise 8 00:02:00 Eye Gymnastics Exercise 9 00:02:00 Eye Gymnastics Exercise 10 00:02:00 Eye Gymnastics Exercise 11 00:02:00 Eye Gymnastics Exercise 12 00:02:00 Bonus Material - Downloads Nutrition for Eye Health 00:00:00

The Power of Vision in the Digital Age What's the secret behind running a successful project? Everyone is looking for the magic bullet, the secret sauce, or the universal solution. It's not just a matter of having the right people on the project, it's also knowing what the vision is and what the purpose behind the vision is. But there is more to it. And what are the challenges and opportunities with running a successful project in the digital age? During this session, we elaborate on this and give you some tips to apply this to your project environment as well. This and other IIL Learning in Minutes presentations qualify for PDUs. Some titles, such as Agile-related topics may qualify for other continuing education credits such as SEUs, or CEUs. Each professional development activity yields one PDU for one hour spent engaged in the activity. Some limitations apply and can be found in the Ways to Earn PDUs section that discusses PDU activities and associated policies. Fractions of PDUs may also be reported. The smallest increment of a PDU that can be reported is 0.25. This means that if you spent 15 minutes participating in a qualifying PDU activity, you may report 0.25 PDU. If you spend 30 minutes in a qualifying PDU activity, you may report 0.50 PDU.