Computer vision courses

295 Courses

Udemy

Automotive Camera [Apply Computer vision, Deep learning] - 1

Enhance your skills in autonomous driving technologies through the Automotive Camera course on Udemy. This program leverages computer vision and deep learning to delve into advanced topics like ADAS, image formation, calibration, object detection, classification, and multi-object tracking using Python. Perfect for those eager to excel in the f.

Microsoft Learn

GitHub responsible AI

Module 1: Introduction to AI Workloads and Azure AI Services. Explore Microsoft's Responsible AI policies and learn about AI solutions and practices for ethical AI. Module 2: Using Azure AI Face. Gain skills in detecting and analyzing faces using Azure AI Face service. Module 3: Foundations of Generative AI. Understand large language mo.

XuetangX

数字化精密测量与智能化

数字化精密测量与智能化技术是实现高精度、高性能高端装备制造的核心所在。本课程通过将理论教学与实验教学相结合，专业知识与思想道德教育相互融合，以及前沿科技和科研成果的整合，旨在培养高端仪器领域的领军人才。提供者: XuetangX 相关领域: 人工智能课程, 计算机视觉课程, 传感器融合课程

Udemy

Cognex In-Sight Machine Vision Industrial Development SCADA

Embark on an enriching journey to master Cognex In-Sight Machine Vision Systems through this expertly crafted programming guide. Offered by Udemy, this course focuses on leveraging Easy Builder for advanced PLC Automation and SCADA Development HMI. Perfect for enthusiasts and professionals alike, the content spans across vital categorie.

Udemy

Object Tracking using Python and OpenCV

Unlock the power of object tracking with Python and OpenCV in this comprehensive course offered by Udemy. Dive into the world of computer vision and learn to implement 12 distinct algorithms designed for tracking objects seamlessly in videos and via webcam. Whether you're a beginner or looking to enhance your skills, this course provides the.

Udemy

YOLO: Custom Object Detection & Web App in Python

Udemy

YOLO: Automatic License Plate Detection & Extract text App

Udemy Embark on a journey to develop a cutting-edge License Plate Detection and Text Extraction Application. This course will guide you through the intricacies of Object Detection using YOLO, mastering Optical Character Recognition (OCR), and crafting a fully functional web application with Flask. Designed for enthusiasts of Artificial Intellig.

Udemy

Deep learning for object detection using Tensorflow 2

Immerse yourself in the field of deep learning and object detection with our expertly crafted course, "Deep Learning for Object Detection using TensorFlow 2". This comprehensive program is designed to provide participants with a solid understanding of how to train and evaluate three advanced models: Faster RCNN, SSD, and YOLO v3, utilizing Te.

Udemy

Intelligently Extract Text & Data from Document with OCR NER

Enhance your skills by participating in the Document Scanner App project focused on intelligently extracting text and data through OCR and NER technologies. Dive deep into the technical realm with OpenCV, Pytesseract, and Spacy to refine your abilities in extracting named entities from scanned documents. Offered by Udemy, this comprehensive co.

Udemy

Data Science & Machine Learning: Naive Bayes in Python

Join the "Data Science & Machine Learning: Naive Bayes in Python" course on Udemy and elevate your understanding of a fundamental AI algorithm. This course is designed to significantly boost your Python programming prowess. This comprehensive program covers the Naive Bayes algorithm, a key technique in data classification and probability theo.

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What is computer vision and what does its developer do?

A computer vision engineer is a specialist who teaches computers to extract information from images. In particular, automatically recognize objects or gestures in images and videos. If a person can visually determine something (for example, find a defect in a product), a computer can also be trained to do this - and thus save time and resources, simplifying many processes.

Developments in the field of computer vision courses are used in a wide variety of companies whose products are related to images or video. This includes the production of self-driving cars, helping doctors interpret MRI images when searching for tumors, and even facial recognition in the subway to identify violators of the self-isolation regime. Computer vision specialists help many e-commerce businesses reduce the burden of moderation: for example, when an ad service like Avito fights trolls who upload pictures with inappropriate content.

Computer vision specialists after computer vision courses are called differently: developers, engineers, and researchers (computer vision scientist). Essentially, a computer vision specialist is more of an engineer who uses mathematics and programming as working tools. So, globally, a computer vision engineer, a computer vision scientist, a computer vision developer and a technical vision developer are one and the same thing.

What does a computer vision developer actually do?

As a rule, the day of such a specialist begins with a stand-up with the team. He then writes code to train neural networks, preprocesses data, and analyzes experiments. A computer vision developer can work alone or in a team, where everyone performs part of a larger task.

As for working tools, the Python language is usually used to write code for experiments, and the Tensorflow or Pytorch frameworks are used to train neural networks. The work also involves special libraries for image processing such as OpenCV. For high-load projects, the C++ language can also be used, since anything written in it is executed many times faster.

Computer vision is a young, dynamically developing field at the intersection of science and engineering, in which there are still more experiments than ready-made solutions. To grow, a specialist here needs to constantly learn. But it is the novelty and non-standard nature of the tasks, as well as the opportunity to create something truly innovative, that brings many people into this profession.

What do they teach in computer vision classes at AI Education?

Training at the best computer vision course typically consists of three modules: creating infrastructure, basics of machine learning and studying computer vision.

The first block at a computer vision online course can be called introductory. Since specialists in the field of computer vision rely on knowledge of mathematics and programming when solving problems, at the start they will have to study from scratch or brush up on topics from higher mathematics, mathematical analysis and linear algebra, as well as work with the Python language. Don’t worry if your knowledge is limited to school mathematics, which was “long ago and not true”: we will help you improve the necessary topics in the first module, so that in the future all students can move through the program at the same rhythm.

The second module is entirely devoted to machine learning. It helps solve computer vision problems faster and easier. For example, for facial recognition, you can expertly describe facial features based on questions that are asked when compiling an identikit. Or you can feed the algorithm a lot of photographic portraits with markings about which face belongs to whom, and then the algorithm itself will learn to extract features by which faces can be identified. In the future, if you need to determine who is in the photo, the algorithm will only need a database of portraits. If there is a photo of the person you need, the system itself will easily find him.

In the second module you will examine probability theory and mathematical statistics. Students will practice solving problems using fundamental algorithms and data structures in Python, become familiar with Python libraries for Data Science (NumPy, Matplotlib), as well as machine learning algorithms.

Finally, in the third module at this machine vision course you will analyze the main tasks of computer vision, we will work with mathematical morphology and the OpenCV and PIL libraries!