Gareth Thomas (MathWorks)
AI, or artificial intelligence, is powering a massive shift in the roles that computers play in our personal and professional lives. Most technical organizations expect to gain or strengthen their competitive advantage through the use of AI. But are you in a position to fulfill that expectation, to transform your research, your products, or your business using AI?
Gareth Thomas looks at the techniques that compose AI (deep learning, computer vision, robotics, and more), enabling you to identify opportunities to leverage it in your work. You will also learn how MATLAB® and Simulink® are giving engineers and scientists AI capabilities that were previously available only to highly-specialized software developers and data scientists.
Michal Blaho (Humusoft)
Interesting changes in MATLAB and Simulink core modules, other extensions and new products.
Jaroslav Jirkovský (Humusoft)
Computer vision uses images and video to detect, classify and track objects or events to understand real-world situations. A variety of methods can be used to do this, from color-based image segmentation, to object detection and tracking, to deep learning methods.
Michal Blaho (Humusoft)
Use of 3D environments for better understanding of situations in the design and simulation of algorithms in robotics and autonomous vehicle control systems. Introduction of new collision detection capabilities.
Jaroslav Jirkovský (Humusoft)
Application of Convolutional Neural Networks (CNN) based deep learning method for image classification and regression tasks. Learning CNNs by transfer learning method and their verification by deep dream visualization technique. Creation of networks with branching architecture (DAG). Detection of objects in image data (R-CNN), semantic image segmentation and data preparation for these tasks (Image Labeler graphical application). Deep learning for time series classification (LSTM networks). Deployment of deep learning models on embedded platforms – code generation in CUDA language.
Jan Studnička (Humusoft)
Presentation of the latest tools in data analytics. MATLAB has grown significantly in this area over the last few years. MATLAB tools allow you to efficiently retrieve, analyze and preprocess data. In MATLAB, one can easily create classification and regression models, optimize model hyperparameters or select significant predictors. At the same time, the same functions can be called on data that does not fit in memory, so-called Big Data.
Jaroslav Jirkovský (Humusoft), Michal Blaho (Humusoft)
Create applications using block diagram and generated code for target platforms such as embedded processors, FPGA, Arduino, Raspberry Pi, Parrot Minidrone, LEGO Mindstorms and others. Using the Model-Based Design method, you can design, simulate and debug a control system and then easily deploy it on an end device. However, the design and debugging of these systems does not have to end with simulation. External debugging, real-time prototyping, HIL simulation and other tools allow you to go beyond the simulation environment. New real-time tuning algorithms can then be deployed directly on embedded hardware and the control system can be continuously modified while the end device is in operation. In a hands-on demonstration, we will introduce the new Arduino Engineering Kit, which guides you through the design of systems using the Model-Based Design method in the form of attractive projects.
Martin Kožíšek (Humusoft)
Presentation of COMSOL Multiphysics and COMSOL Server simulation tools for mathematical simulations of physical processes. The lecture is followed by a COMSOL Multiphysics workshop in the afternoon part of the program.
Jana Sárená (Humusoft)
Introduction of the dSPACE real-time platform. The use of hardware-in-the-loop testing in the automotive industry. Testing of autonomous driving scenarios.
Jan Daněk (Humusoft), Martina Mudrová (Humusoft)
A brief overview of current MATLAB licensing options.
Matěj Pácha (NXP Semiconductors)
Vector control design of permanent magnet synchronous motor without speed/position sensor using Model Based Design Toolbox for S32K – for NXP S32K14× automotive microcontrollers.
Martin Hlaváč, Tomáš Sabáček (Performance Solutions s.r.o.)
Introduction of PS, general experience with Matlab, Matlab and Formula Student – Design of chassis parts (ARB), Yaw moment diagram, creation of aeromaps for calculation of chassis kinematics, calculation of ride heights depending on speed and longitudinal acceleration, calculation of aerodynamic forces acting on the car, work with tyre data, data evaluation – 4 post rig – Martin Hlaváč (Performance Solutions s.r.o.).
Pavel Šedivý (Retia, a.s.)