|
|
USB a FireWire camera aplications
Berka, Petr ; Janáková, Ilona (referee) ; Richter, Miloslav (advisor)
This diploma thesis deals with a interface USB and FireWire cameras to a computer through a technology called DirectShow. I used mostly a development kit „MontiVision“, which cooperates with a programming environment as is e.g. Microsoft Visual C++. You find here how to use a direct pixel access, how to get singles photos from a video, how to set up and calibrate a camera and how can look a particular application of the image processing. I wrote an introduction to the stereo-vision above the frame of my task. This thesis is like a manual for students. It includes my personal experiences and experimentations too.
|
|
| |
|
|
Learning for Classical Planning
Chrpa, Lukáš ; Barták, Roman (advisor) ; Železný, Filip (referee) ; Berka, Petr (referee)
This thesis is mainly about classical planning for artificial intelligence (AI). In planning, we deal with searching for a sequence of actions that changes the environment from a given initial state to a goal state. Planning problems in general are ones of the hardest problems not only in the area of AI, but in the whole computer science. Even though classical planning problems do not consider many aspects from the real world, their complexity reaches EXPSPACE-completeness. Nevertheless, there exist many planning systems (not only for classical planning) that were developed in the past, mainly thanks to the International Planning Competitions (IPC). Despite the current planning systems are very advanced, we have to boost these systems with additional knowledge provided by learning. In this thesis, we focused on developing learning techniques which produce additional knowledge from the training plans and transform it back into planning do mains and problems. We do not have to modify the planners. The contribution of this thesis is included in three areas. First, we provided theoretical background for plan analysis by investigating action dependencies or independencies. Second, we provided a method for generating macro-operators and removing unnecessary primitive operators. Experimental evaluation of this...
|
|
| |
|
| |
|
|
Form, design and thinking of the modern robot
Krajník, Marek ; Berka, Petr (referee) ; Jirků, Petr (advisor)
V této práci bych rád podal popis robota jakožto stroje jak po fyzické, tak po psychické stránce. Budu postupovat od toho, jak by měl vypadat na první pohled a jaké by měl mít funkce, přes úvahu o struktuře konstrukční látky až po to, jak by měl myslet - to bude poslední kapitola, která by se dala také nazvat Umělá Inteligence.
|
|
|
Learning for Classical Planning
Chrpa, Lukáš ; Barták, Roman (advisor) ; Železný, Filip (referee) ; Berka, Petr (referee)
This thesis is mainly about classical planning for artificial intelligence (AI). In planning, we deal with searching for a sequence of actions that changes the environment from a given initial state to a goal state. Planning problems in general are ones of the hardest problems not only in the area of AI, but in the whole computer science. Even though classical planning problems do not consider many aspects from the real world, their complexity reaches EXPSPACE-completeness. Nevertheless, there exist many planning systems (not only for classical planning) that were developed in the past, mainly thanks to the International Planning Competitions (IPC). Despite the current planning systems are very advanced, we have to boost these systems with additional knowledge provided by learning. In this thesis, we focused on developing learning techniques which produce additional knowledge from the training plans and transform it back into planning do mains and problems. We do not have to modify the planners. The contribution of this thesis is included in three areas. First, we provided theoretical background for plan analysis by investigating action dependencies or independencies. Second, we provided a method for generating macro-operators and removing unnecessary primitive operators. Experimental evaluation of this...
|
|
|
AI techniques in algorhitmic trading
Šmejkal, Oldřich ; Pavlíčková, Jarmila (advisor) ; Berka, Petr (referee)
Diploma thesis is focused on research and description of current state of machine learning field, focusing on methods that can be used for prediction and classification of time series, which could be then applied in the algorithmic trading field. Reading of theoretical section should explain basic principles of financial markets, algorithmic trading and machine learning also to reader, which was previously familiar with the subject only very thoroughly. Main objective of application part is to choose appropriate methods and procedures, which match current state of art techniques in machine learning field. Next step is to apply it to historical price data. Result of application of selected methods is determination of their success at out of sample data that was not used during model calibration. Success of prediction was evaluated by accuracy metric along with Sharpe ratio of basic trading strategy that is based on model predictions. Secondary outcome of this work is to explore possibilities and test usability of technologies used in application part. Specifically is tested and used SciPy environment, that combines Python with packages and tools designed for data analysis, statistics and machine learning.
|
|
|
USB a FireWire camera aplications
Berka, Petr ; Janáková, Ilona (referee) ; Richter, Miloslav (advisor)
This diploma thesis deals with a interface USB and FireWire cameras to a computer through a technology called DirectShow. I used mostly a development kit „MontiVision“, which cooperates with a programming environment as is e.g. Microsoft Visual C++. You find here how to use a direct pixel access, how to get singles photos from a video, how to set up and calibrate a camera and how can look a particular application of the image processing. I wrote an introduction to the stereo-vision above the frame of my task. This thesis is like a manual for students. It includes my personal experiences and experimentations too.
|
|
|
Vytvoření predikčního modelu předpovědi počasí pomocí neuronové sítě a asociačních pravidel
Kadlec, Jakub ; Rauch, Jan (advisor) ; Berka, Petr (referee)
This diploma thesis introduces three different methods of creating a neural network binary classifier for the purpose of automated weather prediction with attribute pre-selection using association rules and correlation patters mining by the LISp-Miner system. First part of the thesis consists of collection of theoretical knowledge enabling the creation of such predictive model, whereas the second part describes the creation of the model itself using the CRISP-DM methodology. Final part of the thesis analyses the performance of created classifiers and concludes the proposed methods and their possible benefits over training the network without attribute pre-selection.
|
guest ::
RSS feed.