Vom 28. November bis 2. Dezember 2022 findet in Berlin und online die ML Con - das Event für Machine Learning Technologien und Innovationen - statt.
Image recognition is the parade discipline of machine learning. Artificial neural networks can achieve recognition rates and robustness that were unthinkable with classical methods. However, traditional approaches are still useful in some areas as an alternative or in combination with neural networks. In this talk, I take you through the following topics:
1. traditional approaches: What are these approaches? What is their strength and what are their limitations?
2. neural networks: When are they useful and in what architecture? What does it take to train them?
3. what’s next: Newer approaches that have not yet been tested in practical applications, but have potential to play a larger role in the future.
Recognizing what is in an image is a common task. Applications range from simple classification to extracting multiple objects even in video.In the Python world there are two standard libraries for this. On one hand there is OpenCV for classic image processingand on the other hand we have TensorFlow with its Keras API for the machine learning to do pattern matching.In this hands-on workshop you will learn when to use which library and how to use it.