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Road Sign Detection from Camera in Car
Dušek, Jan ; Sochor, Jakub (referee) ; Beran, Vítězslav (advisor)
This bachelor's thesis is focused on detection of traffic signs from image or video. Algorithms common for object detection will be introduced in the beginning. Description of object detection using histogram of oriented gradients and support vector machines will follow. Last part will present accomplished results.
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Analysis of the effect of delay and window size on TCP connection efficiency
Kavický, Martin ; Komosný, Dan (referee) ; Molnár, Karol (advisor)
Content of master’s thesis is description field of Sliding window and it’s expansion algorithms, witch are Slow start, Congestion avoidance, Fast Retransmit and Fast Recovery algorithm. Thereinafter is described creation of model in Opnet Modeler’s simulation area. In this simulation area was analyzed reactions of average transfer speed onto variance of data size, lost ratio, latency in short and long time slot and variance of receiver’s buffer size. In last section of this document is method design witch makes it possible of transfer speed control through the use of receiver’s buffer size dynamic setting.
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Re-Identification of Vehicles by License Plate Recognition
Špaňhel, Jakub ; Juránková, Markéta (referee) ; Herout, Adam (advisor)
This thesis aims at proposing vehicle license plate detection and recognition algorithms, suitable for vehicle re-identification. Simple urban traffic analysis system is also proposed. Multiple stages of this system was developed and tested. Specifically - vehicle detection, license plate detection and recognition. Vehicle detection is based on background substraction method, which results in an average hit rate of ~92%. License plate detection is done by cascade classifiers and achieves an average hit rate of 81.92% and precision rate of 94.42%. License plate recognition based on Template matching results in an average precission rate of 60.55%. Therefore the new license plate recognition method based on license plate scanning using the sliding window principle and neural network recognition was introduced. Neural network achieves a precision rate of 64.47% for five input features. Low precision rate of neural network is caused by small amount of training sample for some specific license plate characters.
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Handwritten text recognition using a sliding window
Ďuriš, Denis ; Povoda, Lukáš (referee) ; Rajnoha, Martin (advisor)
This bachelor thesis deals with optical character recognition. It focuses on recognizing hand-written text. The theoretical introduction describes the methods used for optical character recognition and selected machine learning methods. Subsequently, the work describes two methods for making cutouts of characters, using a sliding window. Cutouts are used in training and testing datasets of machine learning models. The document includes methods to improve the accuracy of character recognition. The accuracy of the models is evaluated in conclusion. Charcters in cutouts are clasified by an automated recognition program.
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Searching repetitive DNA in nucleotide sequences
Moskovská, Kateřina ; Provazník, Ivo (referee) ; Kubicová, Vladimíra (advisor)
This bachelor thesis deals with problem of repetitive DNA and algorithms for searching tandem repeats. Tandem repeats are important for biological industry. They are used as gene marker for creating genetic maps, profiles of DNA for paternity testing and in forensic sphere. Tandem repeats wreak several sever humen illness and it is another reason for their searching. Therefore are algorithms for searching of tandem repeats objects of many studies. We can divided algorithms to two main groups – algorithms based on string matching and algorithms based on digital signal processing. Task of this bachelor thesis is choose one member of each group and propose their implementation and than implement them in program Matlab. Result of this thesis should be comparison both programs. This comparison pass off on the basis of chosen criterion and several sequences. Both program transform these sequences and than can be programs compare.
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Suffix Graphs and Lossless Data Compression
Senft, Martin ; Dvořák, Tomáš (advisor) ; Dvorský, Jiří (referee) ; Smyth, William F. (referee)
Title: Suffix Graphs and Lossless Data Compression Author: Martin Senft Department: Department of Software and Computer Science Education Supervisor of the doctoral thesis: doc. RNDr. Tomáš Dvorˇák, CSc., Depart- ment of Software and Computer Science Education Abstract: Suffix tree and its variants are widely studied data structures that enable an efficient solution to a number of string problems, but also serve for implementation of data compression algorithms. This work explores the opposite approach: design of compression methods, based entirely on prop- erties of suffix graphs. We describe a unified construction algorithm for suf- fix trie, suffix tree, DAWG and CDAWG, accompanied by analysis of implicit suffix link simulation that yields two practical alternatives. Since the com- pression applications require maintaining text in the sliding window, an in- depth discussionof slidingsuffixgraphsisneeded. Fillinggapsin previously published proofs, we verify that suffix tree is capable of perfect sliding in amortised constant time. On the other hand, we show that this is not the case with CDAWG, thus resolving a problem of Inenaga et al. Building on these investigations,we describea family of data compression methods,based on a description of suffix tree construction for the string to be compressed. While some of...
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Handwritten text recognition using a sliding window
Ďuriš, Denis ; Povoda, Lukáš (referee) ; Rajnoha, Martin (advisor)
This bachelor thesis deals with optical character recognition. It focuses on recognizing hand-written text. The theoretical introduction describes the methods used for optical character recognition and selected machine learning methods. Subsequently, the work describes two methods for making cutouts of characters, using a sliding window. Cutouts are used in training and testing datasets of machine learning models. The document includes methods to improve the accuracy of character recognition. The accuracy of the models is evaluated in conclusion. Charcters in cutouts are clasified by an automated recognition program.
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Re-Identification of Vehicles by License Plate Recognition
Špaňhel, Jakub ; Juránková, Markéta (referee) ; Herout, Adam (advisor)
This thesis aims at proposing vehicle license plate detection and recognition algorithms, suitable for vehicle re-identification. Simple urban traffic analysis system is also proposed. Multiple stages of this system was developed and tested. Specifically - vehicle detection, license plate detection and recognition. Vehicle detection is based on background substraction method, which results in an average hit rate of ~92%. License plate detection is done by cascade classifiers and achieves an average hit rate of 81.92% and precision rate of 94.42%. License plate recognition based on Template matching results in an average precission rate of 60.55%. Therefore the new license plate recognition method based on license plate scanning using the sliding window principle and neural network recognition was introduced. Neural network achieves a precision rate of 64.47% for five input features. Low precision rate of neural network is caused by small amount of training sample for some specific license plate characters.
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Searching repetitive DNA in nucleotide sequences
Moskovská, Kateřina ; Provazník, Ivo (referee) ; Kubicová, Vladimíra (advisor)
This bachelor thesis deals with problem of repetitive DNA and algorithms for searching tandem repeats. Tandem repeats are important for biological industry. They are used as gene marker for creating genetic maps, profiles of DNA for paternity testing and in forensic sphere. Tandem repeats wreak several sever humen illness and it is another reason for their searching. Therefore are algorithms for searching of tandem repeats objects of many studies. We can divided algorithms to two main groups – algorithms based on string matching and algorithms based on digital signal processing. Task of this bachelor thesis is choose one member of each group and propose their implementation and than implement them in program Matlab. Result of this thesis should be comparison both programs. This comparison pass off on the basis of chosen criterion and several sequences. Both program transform these sequences and than can be programs compare.
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Road Sign Detection from Camera in Car
Dušek, Jan ; Sochor, Jakub (referee) ; Beran, Vítězslav (advisor)
This bachelor's thesis is focused on detection of traffic signs from image or video. Algorithms common for object detection will be introduced in the beginning. Description of object detection using histogram of oriented gradients and support vector machines will follow. Last part will present accomplished results.
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