OpenCV Tutorials - Computer Vision

This lecture introduces serverless systems through AWS Lambda, and creates an image processing end system with OpenCV, an image processing library, and expands it with an API.

Let's create a web app that uploads an image and uses OpenCV to process it and detect faces.

This is an introductory course on OpenCV using C#. It mainly covers how to use functions, how function arguments affect results, etc., rather than theoretical elements.

Easy, Usable Computer Vision Projects: Step-by-step learning of practical CV projects. Boost skill with real examples.

This is a newly designed course that allows you to gradually learn the mathematics, theory, PyTorch-based implementation, transfer learning, and GPT's core transformer needed to understand deep learning, based on the instructor's own failed experiences when first learning deep learning.

This course allows you to build an AI portfolio by cloning the Amenity Detection project from the Airbnb Data Science team—a prime example of TensorFlow utilization—and documenting the entire process on a GitHub blog.

AI Artificial Intelligence, it goes without saying that mobile is the trend. But how do you learn machine learning and deep learning and use them on mobile? Now, let's learn useful mobile Computer Vision projects that are used in daily life.

This course is a specialized program that covers practical application strategies for utilizing artificial intelligence (AI) in the construction and civil engineering fields. In the construction industry where digital transformation is accelerating, AI is driving innovation across design, construction, safety, and quality management. This course focuses on learning practical application cases that can be utilized in actual field sites, including smart construction, digital twins, AI-based equipment control, safety monitoring, and quality verification.

The electronics and semiconductor industry is a field where data-driven management and innovation are particularly crucial due to ultra-precision processes and complex supply chains. This course covers practical strategies that can be directly applied in electronics and semiconductor manufacturing, including defect detection, process optimization, predictive maintenance, and supply chain management using AI technology. Along with real-world cases from global companies, the course also presents low-cost, high-efficiency AI implementation methods that small and medium-sized enterprises can realistically utilize. Through this, students will be able to understand and apply AI-based manufacturing strategies that not only improve productivity and reduce costs, but also build future competitiveness.

Let's create a web app that uploads an image and uses OpenCV to process it and detect faces.

This is a comprehensive machine learning project course that learns various useful machine learning regression and classification projects along with theory using Python and TensorFlow 2 based on Boston Marathon big data.

When researching AI or conducting a project using it, basic paper implementation is essential. Let's upgrade our practical skills by implementing an actual paper through this lecture!

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