THE EFFECT OF DIFFERENT FORMS OF OXYGEN ON PROPERTIES OF BETA TITANIUM ALLOYS

The beta-titanium alloys are widely used in many applications (medicine, aerospace industry etc.) due to their superior properties, such as corrosion resistance, biocompatibility and high strength to weight ratio. One of the ways how to increase the strength of those alloys is the addition of oxygen. The oxygen can be present in various forms in the alloy – in a solid solution or in the form of oxides. In this work, the effect of two forms of oxygen (i.e., solid solution and dispersion particles) was studied. Two alloys, one arc melted with different oxygen additions and one prepared via powder metallurgy where the titanium powder was oxidized, were prepared. The microstructure and mechanical properties were studied. A significant increase in strength with increasing the oxygen content in the solid solution has been observed. However, the powder oxidation has almost no effect on a tensile strength probably due to quite large interparticle distances between titanium oxide particles

Interactive video retrieval evaluation at a distance: comparing sixteen interactive video search systems in a remote setting at the 10th Video Browser Showdown

The Video Browser Showdown addresses difficult video search challenges through an annual interactive evaluation campaign attracting research teams focusing on interactive video retrieval. The campaign aims to provide insights into the performance of participating interactive video retrieval systems, tested by selected search tasks on large video collections. For the first time in its ten year history, the Video Browser Showdown 2021 was organized in a fully remote setting and hosted a record number of sixteen scoring systems. In this paper, we describe the competition setting, tasks and results and give an overview of state-of-the-art methods used by the competing systems. By looking at query result logs provided by ten systems, we analyze differences in retrieval model performances and browsing times before a correct submission. Through advances in data gathering methodology and tools, we provide a comprehensive analysis of ad-hoc video search tasks, discuss results, task design and methodological challenges. We highlight that almost all top performing systems utilize some sort of joint embedding for text-image retrieval and enable specification of temporal context in queries for known-item search. Whereas a combination of these techniques drive the currently top performing systems, we identify several future challenges for interactive video search engines and the Video Browser Showdown competition itself

Modely podobnosti pro content-based video retrieval

Multimedia retrieval is increasingly important with the skyrocketing multimedia vol- umes produced every day. Therefore many image and video retrieval tools are being developed utilising visual similarity modelling algorithms for similar image retrieval or various visualisations. As such, the quality of the similarity modelling is crucial for these tools. This thesis explores diverse similarity models, their agreement with human percep- tion of similarity and possible improvements of these models. The examined similarity models consisted of colour-based, SIFT-based, and DNN-based models. For the purpose of model evaluation, a user study was conducted to create a dataset of relative image similarity comprising both generic images as well as two compact domains. In this study, the participants were asked to state which of the candidate images was more similar to the query image. The collected data showed the superiority of DNN-based models compared to other evaluated variants. Nonetheless, all similarity models performed significantly better than a random guess. In order to further enhance the performance of the simi- larity models, we fine-tuned the best-performing model (W2VV++) with the collected dataset and achieved significant improvement in some areas. 1Vyhledávání multimédií je stále důležitější vzhledem k prudce rostoucímu objemu mul- timediálního obsahu. Proto je vyvíjeno mnoho nástrojů pro vyhledávání obrázků a videí, které využívají algoritmy modelování vizuální podobnosti pro vyhledávání podobných obrázků nebo tvorbu různých vizualizací. Tím pádem kvalita modelování podobnosti je pro tyto nástroje klíčová. Tato práce zkoumá různé modely podobnosti, jejich shodu s lidskými anotacemi a potenciální zlepšení. Do studie byly zahrnuty 3 třídy modelů podobnosti: modely založených na barvách, SIFTu nebo hlubokých neuronových sítí. Za tímto účelem byla provedena uživatelská studie s cílem vytvořit dataset relativních podob- ností obrázků s obecnými i specifickými obrázky. V této studii byli účastníci požádáni, aby vždy vybrali mezi dvěma možnostmi tu, která byla podobnější hlavnímu obrázku. Shromážděná data ukázala lepší výsledky modelů založených na hlubokých neuronových sítích ve srovnání s ostatními hodnocenými variantami. Nicméně všechny modely podob- nosti si vedly výrazně lépe než náhodný odhad. Abychom dále zvýšili přesnost modelů podobnosti, vyladili jsme model W2VV++ pomocí získaného datasetu. Díky tomu jsme v některých doménách dosáhli výrazného zlepšení. 1Department of Software EngineeringKatedra softwarového inženýrstvíFaculty of Mathematics and PhysicsMatematicko-fyzikální fakult

Viktor Fischl: Czech and Israel personality

Předmětem mé bakalářské práce je především snaha zmapovat a analyzovat život a dílo českého spisovatele a diplomata Viktora Fischla. Cílem práce bylo věnovat se Fischlově literární tvorbě a podrobně ji kriticky rozebrat na základě komparace s autobiografickými prvky ze života autora. Zvolená literární díla jsou tvořena souborem několika motivických prvků, které v práci rozkrývám a definuji tak díla v kontextu s literárním teoretickým rámcem a analyzuji jejich intertextuální odkazy.The subject of my bachelor degree is mainly an attempt to fully describe and to analyse the stories and life of Czech writer and diplomat Viktor Fischl. My intention was to deal with his works and dissect it particulary based on comparison with autobiographical element from the writer?s life. Those pieces which I?ve chosen are formed by a collection of some motivating elements, which I describe and define those pieces in context with theoretical literal frame and analyse their intertextuality links.Katedra historických vědDokončená práce s úspěšnou obhajobo

Known-item search with relevance to SOM feedback

Multimedia searching is usually realized by means of text search, where a large dataset is sorted with respect to a relevance to a given text query. However, if users search for just one scene or image, a sequential browsing of a larger result set is often necessary, without a guarantee that the object is found in a reasonable time. This work focuses on methods relying on relevance feedback for more effective searching in a large collection of one million images. Several relevance update and display selection approaches are compared using simulations of relevance feedback. Our experiments reveal that the investigated models are a benefit to modern multimedia search engines.

Similarity Models for Content-based Video Retrieval

Multimedia retrieval is increasingly important with the skyrocketing multimedia vol- umes produced every day. Therefore many image and video retrieval tools are being developed utilising visual similarity modelling algorithms for similar image retrieval or various visualisations. As such, the quality of the similarity modelling is crucial for these tools. This thesis explores diverse similarity models, their agreement with human percep- tion of similarity and possible improvements of these models. The examined similarity models consisted of colour-based, SIFT-based, and DNN-based models. For the purpose of model evaluation, a user study was conducted to create a dataset of relative image similarity comprising both generic images as well as two compact domains. In this study, the participants were asked to state which of the candidate images was more similar to the query image. The collected data showed the superiority of DNN-based models compared to other evaluated variants. Nonetheless, all similarity models performed significantly better than a random guess. In order to further enhance the performance of the simi- larity models, we fine-tuned the best-performing model (W2VV++) with the collected dataset and achieved significant improvement in some areas.

On the User-centric Comparative Remote Evaluation of Interactive Video Search Systems

In the research of video retrieval systems, comparative assessments during dedicated retrieval competitions provide priceless insights into the performance of individual systems. The scope and depth of such evaluations are unfortunately hard to improve, due to the limitations by the set-up costs, logistics, and organization complexity of large events. We show that this easily impairs the statistical significance of the collected results, and the reproducibility of the competition outcomes. In this article, we present a methodology for remote comparative evaluations of content-based video retrieval systems and demonstrate that such evaluations scale-up to sizes that reliably produce statistically robust results, and propose additional measures that increase the replicability of the experiment. The proposed remote evaluation methodology forms a major contribution toward open science in interactive retrieval benchmarks. At the same time, the detailed evaluation reports form an interesting source of new observations about many subtle, previously inaccessible aspects of video retrieval

On the User-centric Comparative Remote Evaluation of Interactive Video Search Systems

In the research of video retrieval systems, comparative assessments during dedicated retrieval competitions provide priceless insights into the performance of individual systems. The scope and depth of such evaluations is unfortunately hard to improve, due to the limitations by the set-up costs, logistics and organization complexity of large events. We show that this easily impairs the statistical significance of the collected results, and the reproducibility of the competition outcomes. In this paper, we present a methodology for remote comparative evaluations of content-based video retrieval systems and demonstrate that such evaluations scale-up to sizes that reliably produce statistically robust results, and propose additional measures that increase the replicability of the experiment. The proposed remote evaluation methodology forms a major contribution towards open science in interactive retrieval benchmarks. At the same time, the detailed evaluation reports form an interesting source of new observations about many subtle, previously inaccessible aspects of video retrieval