Get a comprehensive overview of Object Detection 101 Course - Including 4xProjects | Computer Vision

This course provides a unique opportunity for new learners to develop their own computer vision flask desktop application project using machine learning, Python, and deploy it in the cloud. Learners will be guided through the process of installing Python and the necessary libraries, as well as learning image processing techniques in OpenCV and the mathematical concepts behind the images. They will also learn how to extract features from images using deep neural networks, train different deep learning models like convolutional neural networks, and write code for performing predictions with the CNN model. Finally, learners will develop a desktop application and make predictions to live video streaming. With Face Mask Recognition: Deep Learning based Desktop App, learners can gain the skills to build their own computer vision project and deploy it in the cloud.

This course provides a comprehensive guide to mastering facial recognition in .NET/C# using Aforge and Accord. It offers a step-by-step approach to learning, with detailed audio and visual presentations, and provides learners with the knowledge to design and develop other types of object/shape detection. Learners will gain an understanding of project setup, image filters, shape and face detection, camera and picture validation, background detection, and user interface design. Additionally, learners will gain insight into different use cases of the learning outcomes for desktop applications, web solutions, and service-oriented architecture. Click this course to master facial recognition in .NET/C# using Aforge and Accord.

This course is the ultimate guide for beginners to learn about face detection and recognition techniques. It covers topics such as detection of faces using Haarcascade, HOG, MMOD, and SSD, as well as detection of other objects, such as eyes, smiles, clocks, bodies, and cars. It also covers recognition of faces using Eigenfaces, Fisherfaces, LBPH, and advanced Deep Learning techniques. Learners will learn how to compare the performance of the algorithms and build their custom dataset capturing faces via webcam. With more than 60 lectures and 8 hours of step by step videos, this course is the perfect way to get started with facial detection and recognition.