“Perelik Soft helped us significantly not only with making first steps in the machine learning area as a company, but also with making use of ML models in production.”
Maxime Regh, Director Fraud Prevention, cleverbridge AG
We conduct interviews with your team to understand your goals
Together we localise the data for initial experiments
We conduct the research and initial experiments
Presentation of the results and recommendations for next steps
Read more on the topic in our blog
AI applications often involve not only classical application engineering but also elements of research (Fig. 1). Sometimes it is not clear from the start which approach will be better and one needs to conduct experiments to evaluate multiple approaches.
Autonomous vehicles (AVs) have been developing at a very high rate in recent years. They are expected to reach a full level of autonomy (level 5) very soon. The main technology for creating autonomous vehicles is Artificial Intelligence (AI) and in particular its subcategories Machine Learning (ML) and Deep Learning (DL).
In this article we will look at the application of Machine learning algorithms in autonomous vehicles.
Computer vision is a field that has undergone great development in recent years and it is becoming more widespread, both among the industry, as well as in everyday activities and consumer/user applications.
The goal of this post/article is to help researchers, developers and enthusiasts involved in computer vision to gain an overview over some of the most popular and widely used software libraries and tools in this field.