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Content-based exploration of unstructured data
Čech, Přemysl ; Lokoč, Jakub (advisor) ; Barthel, Kai Uwe (referee) ; Gudmundsson, Gylfi Thor (referee)
Effective analysis, searching and browsing throughout arbitrary multimedia collections is still a challenging task. To perform a search among multimedia objects, first, a similarity model has to be defined. Such a model establishes methods describing how the content of individual objects is processed and how key features and descriptors, that are used for modeling similarity between objects, are formed. This task is not trivial since there can be many ways of determining how to comprehend the content of multimedia data. Furthermore, with the growing size of contemporary database collections, multimedia retrieval and exploration are extremely computationally intensive. Hence, researchers investigate support indexing structures that can evaluate similarity queries and can respond to user's queries in almost real-time even on datasets counting billions of objects. Another very important aspect of a retrieval system is the user interface for defining queries as well as presenting retrieved results. A multimedia system should offer various inputs for formulating user's queries, especially for situations in which a user cannot provide an ideal query example. Finally, a well- arranged and easy to read interface for visualization of retrieved results is essential for the success of a multimedia exploration and...
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Comparison of signature-based and semantic similarity models
Kovalčík, Gregor ; Lokoč, Jakub (advisor) ; Mráz, František (referee)
Content-based image retrieval and similarity search has been investigated for several decades with many different approaches proposed. This thesis fo- cuses on a comparison of two orthogonal similarity models on two different im- age retrieval tasks. More specifically, traditional image representation models based on feature signatures are compared with models based on state-of-the-art deep convolutional neural networks. Query-by-example benchmarking and tar- get browsing tasks were selected for the comparison. In a thorough experimental evaluation, we confirm that models based on deep convolutional neural networks outperform the traditional models. However, in the target browsing scenario, we show that the traditional models could still represent an effective option. We have also implemented a feature signature extractor into the OpenCV library in order to make the source codes available for the image retrieval and computer vision community. 1
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Aplikace umělých neuronových sítí pro detekci malware v HTTPS komunikaci
Bodnár, Jan ; Lokoč, Jakub (advisor) ; Somol, Petr (referee)
A huge proportion of modern malicious software uses Internet connec- tions. Therefore, it is possible to detect infected computers by inspecting network activity. Since attackers hide the content of communication by com- municating over encrypted protocols such as HTTPS, communication must be analysed purely on the basis of metadata. Cisco provided us a dataset containing aggregated metadata with additional information as to whether or not each sample contains malicious communication. This work trains neu- ral networks to distinguish between infected and benign samples, comparing different architectures of neural networks and providing a comparison with results achieved by different machine learning methods tried by colleagues. It also seeks to create a mapping which maps samples of communication into a space where different samples of malicious communication created by a sin- gle malware family form clusters. This may make it easier to find different computers infected by a virus with known behaviour, even when the virus cannot be detected by the detection system. 1
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The Impact of Image Resolution on the Precision of Content-based Retrieval
Navrátil, Lukáš ; Lokoč, Jakub (advisor) ; Skopal, Tomáš (referee)
This thesis is focused on comparing methods for similarity image retrieval. Common techniques and testing sets are introduced. The testing sets are there to measure the accuracy of the searching systems based on similarity image retrieval. Measurements are done on those models which are implemented on the basis of presented techniques. These measurements examine their results depending on the input data, used components and parameters settings, especially the impact of image resolution on the retrieval precision is examined. These results are analysed and the models are compared. Powered by TCPDF (www.tcpdf.org)
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Exploration of Multimedia Collections
Moško, Juraj ; Skopal, Tomáš (advisor) ; Schöffmann, Klaus (referee) ; Dohnal, Vlastislav (referee)
Multimedia retrieval systems are supposed to provide the method and the interface for users to retrieve particular multimedia data from multimedia collections. Although, many different retrieval techniques evolved from times when the search in multimedia collections firstly appeared as a research task, not all of them can fulfill specific requirements that the multimedia exploration is determined for. The multimedia exploration is designated for revealing the content of a whole multimedia collection, quite often totally unknown to the users who retrieve data. Because of these facts a multimedia exploration system has to solve problems like, how to visualize (usually multidimensional) multimedia data, how to scale data retrieval from arbitrarily large collections and how to design such an interface that the users could intuitively use for the exploration. Taking these problems into consideration, we proposed and evaluated ideas for building the system that is well-suited for the multimedia exploration. We outlined the overall architecture of a multimedia exploration system, created the Multi-Layer Exploration Structure (MLES) as an underlying index structure that should solve problems of efficient and intuitive data retrieval and we also proposed definitions of exploration operations as an interactive and...
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Exploration of Multimedia Collections
Moško, Juraj ; Skopal, Tomáš (advisor)
Multimedia retrieval systems are supposed to provide the method and the interface for users to retrieve particular multimedia data from multimedia collections. Although, many different retrieval techniques evolved from times when the search in multimedia collections firstly appeared as a research task, not all of them can fulfill specific requirements that the multimedia exploration is determined for. The multimedia exploration is designated for revealing the content of a whole multimedia collection, quite often totally unknown to the users who retrieve data. Because of these facts a multimedia exploration system has to solve problems like, how to visualize (usually multidimensional) multimedia data, how to scale data retrieval from arbitrarily large collections and how to design such an interface that the users could intuitively use for the exploration. Taking these problems into consideration, we proposed and evaluated ideas for building the system that is well-suited for the multimedia exploration. We outlined the overall architecture of a multimedia exploration system, created the Multi-Layer Exploration Structure (MLES) as an underlying index structure that should solve problems of efficient and intuitive data retrieval and we also proposed definitions of exploration operations as an interactive and...
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Signature-based video browser
Blažek, Adam ; Lokoč, Jakub (advisor) ; Kruliš, Martin (referee)
In this thesis, we present an effective yet efficient approach for Known-Item Search in video data. The approach utilizes so called feature signatures - simple and flexible visual descriptors based on color distribution. The feature signatures enable to efficiently represent video key-frames and at the same time allow users to intuitively draw simple colored sketches of the searched scenes. In the thesis, we describe in detail a novel video retrieval model and also discuss and carefully optimize it's parameters. To achieve high efficiency, we expose several indexing techniques suitable for the model and empirically evaluate their performance in the experiments. The described model is implemented in C# programming language with simple and intuitive user interface enabling users to~ interactively browse up to tens of hours of video. Powered by TCPDF (www.tcpdf.org)
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Satellite data management and analysis
Krška, David ; Lokoč, Jakub (advisor) ; Nečaský, Martin (referee)
The aim of this bachelor thesis is to implement and test an interactive application for the analysis, visualization and classification of satellite data. The satellite data are preprocessed and automatically composed into colored images. The application allows to create and compare two types of classification algorithms. The first type uses single images and the second type uses multiple images of the same place, but at different times. We also created an interface for selecting and managing the training data. A few well-known classification algorithms of both types were implemented and their success rates were compared in an experiment. All the satellite data used in the experiment are from the Landsat program. The result of this bachelor thesis is an application primarily focused on classification. But the application could also be extended into a complex GIS system. Powered by TCPDF (www.tcpdf.org)
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Employing Parallel Architectures in Similarity Search
Kruliš, Martin ; Yaghob, Jakub (advisor) ; Platoš, Jan (referee) ; Pllana, Sabri (referee)
This work examines the possibilities of employing highly parallel architectures in database systems, which are based on the similarity search paradigm. The main objective of our research is utilizing the computational power of current GPU devices for similarity search in the databases of images. Despite leaping progress made in the past few years, the similarity search problems remain very expensive from a compu- tational point of view, which limits the scope of their applicability. GPU devices have a tremendous computational power at their disposal; however, the usability of this power for particular problems is often complicated due to the specific properties of this architecture. Therefore, the existing algorithms and data structures require extensive modifications if they are to be adapted for the GPUs. We have addressed all the aspects of this domain, such as efficient utilization of the GPU hardware for generic computations, parallelization of similarity search process, and acceleration of image indexing techniques. In most cases, employing the GPU devices brought a speedup of two orders of magnitude with respect to single-core CPUs and approximately one order of magnitude with respect to multiprocessor NUMA servers. This thesis summarizes our experience and discoveries from several years of research,...
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Ontological Reasoning with Taxonomies in RDF Database
Hoferek, Ondřej ; Nečaský, Martin (advisor) ; Svoboda, Martin (referee)
13548805670613-46162052c208770f99e83a586780d16c.txt As the technologies for the realisation of the idea of the Semantic Web have evolved rapidly during past few years, it is possible to use them in variety of applications. As they are designed with the ability to process and analyze semantic information found in the data in mind, they are particularly suitable for the task of enhancing relevance of the document retrieval. In this work, we discuss the possibilities of identifying a suitable subset of the expressing capabilities of the SPARQL querying language and create a component that encapsulates the technical details of its usage. Page 1
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