6 research outputs found

    Pedestrian Localization Using Images

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    Cílem této práce je seznámení s metodami pro lokalizaci chodců, které jsou již v dnešní době všude okolo nás a pomáhají lidem zlepšovat život. V budoucnu budou takové metody nedílnou součástí každodenního života. Práce se bude zejména zaměřovat na konkrétní metody, srovnání přesnosti a časové náročnosti mezi sebou. Implementace detektorů pro detekci jednotlivých chodců bude v různých knihovnách pro jazyk Python. Trénink modelů bude z množiny snímků z datasetů ECP, Cityscapes a PRW. Testování jejich funkčnosti bude následně otestováno na množinách snímků ECP datasetu a Cityscapes datasetu.The goal of this work is to get acquainted with methods for locating pedestrians which are already all around us today and help people improve their lives. In the future, such methods will be an integral part of everyday life. The work will mainly focus on specific methods, comparison of accuracy and time requirements among themselves. The implementation of detectors for the detection of individual pedestrians will be in different libraries for the Python language. The training of the models will be from a set of images from the ECP, Cityscapes and PRW datasets. Testing their functionality will subsequently be tested on sets of images of the ECP dataset and the Cityscapes dataset.460 - Katedra informatikyvelmi dobř

    Low but contrasting neutral genetic differentiation shaped by winter temperature in European great tits

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    Gene flow is usually thought to reduce genetic divergence and impede local adaptation by homogenising gene pools between populations. However, evidence for local adaptation and phenotypic differentiation in highly mobile species, experiencing high levels of gene flow, is emerging. Assessing population genetic structure at different spatial scales is thus a crucial step towards understanding mechanisms underlying intraspecific differentiation and diversification. Here, we studied the population genetic structure of a highly mobile species – the great tit Parus major – at different spatial scales. We analysed 884 individuals from 30 sites across Europe including 10 close-by sites (< 50 km), using 22 microsatellite markers. Overall we found a low but significant genetic differentiation among sites (FST = 0.008). Genetic differentiation was higher, and genetic diversity lower, in south-western Europe. These regional differences were statistically best explained by winter temperature. Overall, our results suggest that great tits form a single patchy metapopulation across Europe, in which genetic differentiation is independent of geographical distance and gene flow may be regulated by environmental factors via movements related to winter severity. This might have important implications for the evolutionary trajectories of sub-populations, especially in the context of climate change, and calls for future investigations of local differences in costs and benefits of philopatry at large scales

    Low but contrasting neutral genetic differentiation shaped by winter temperature in European great tits

    No full text
    Gene flow is usually thought to reduce genetic divergence and impede local adaptation by homogenising gene pools between populations. However, evidence for local adaptation and phenotypic differentiation in highly mobile species, experiencing high levels of gene flow, is emerging. Assessing population genetic structure at different spatial scales is thus a crucial step towards understanding mechanisms underlying intraspecific differentiation and diversification. Here, we studied the population genetic structure of a highly mobile species - the great tit Parus major - at different spatial scales. We analysed 884 individuals from 30 sites across Europe including 10 close-by sites (< 50 km), using 22 microsatellite markers. Overall we found a low but significant genetic differentiation among sites (FST = 0.008). Genetic differentiation was higher, and genetic diversity lower, in south-western Europe. These regional differences were statistically best explained by winter temperature. Overall, our results suggest that great tits form a single patchy metapopulation across Europe, in which genetic differentiation is independent of geographical distance and gene flow may be regulated by environmental factors via movements related to winter severity. This might have important implications for the evolutionary trajectories of sub-populations, especially in the context of climate change, and calls for future investigations of local differences in costs and benefits of philopatry at large scales

    Data from: Low but contrasting neutral genetic differentiation shaped by winter temperature in European great tits

    No full text
    Gene flow is usually thought to reduce genetic divergence and impede local adaptation by homogenising gene pools between populations. However, evidence for local adaptation and phenotypic differentiation in highly mobile species, experiencing high levels of gene flow, is emerging. Assessing population genetic structure at different spatial scales is thus a crucial step towards understanding mechanisms underlying intraspecific differentiation and diversification. Here, we studied the population genetic structure of a highly mobile species – the great tit Parus major – at different spatial scales. We analysed 884 individuals from 30 sites across Europe including 10 close-by sites (< 50 km), using 22 microsatellite markers. Overall we found a low but significant genetic differentiation among sites (FST = 0.008). Genetic differentiation was higher, and genetic diversity lower, in south-western Europe. These regional differences were statistically best explained by winter temperature. Overall, our results suggest that great tits form a single patchy metapopulation across Europe, in which genetic differentiation is independent of geographical distance and gene flow may be regulated by environmental factors via movements related to winter severity. This might have important implications for the evolutionary trajectories of sub-populations, especially in the context of climate change, and calls for future investigations of local differences in costs and benefits of philopatry at large scales

    Data from: Low but contrasting neutral genetic differentiation shaped by winter temperature in European great tits

    No full text
    Gene flow is usually thought to reduce genetic divergence and impede local adaptation by homogenising gene pools between populations. However, evidence for local adaptation and phenotypic differentiation in highly mobile species, experiencing high levels of gene flow, is emerging. Assessing population genetic structure at different spatial scales is thus a crucial step towards understanding mechanisms underlying intraspecific differentiation and diversification. Here, we studied the population genetic structure of a highly mobile species – the great tit Parus major – at different spatial scales. We analysed 884 individuals from 30 sites across Europe including 10 close-by sites (< 50 km), using 22 microsatellite markers. Overall we found a low but significant genetic differentiation among sites (FST = 0.008). Genetic differentiation was higher, and genetic diversity lower, in south-western Europe. These regional differences were statistically best explained by winter temperature. Overall, our results suggest that great tits form a single patchy metapopulation across Europe, in which genetic differentiation is independent of geographical distance and gene flow may be regulated by environmental factors via movements related to winter severity. This might have important implications for the evolutionary trajectories of sub-populations, especially in the context of climate change, and calls for future investigations of local differences in costs and benefits of philopatry at large scales. The data package contains one dataset: - This file contains the combined dataset collected on great tits (Parus major) from 30 sites in Europe. Provided are individual data for microsatellites (GenData) and environmental data by site (EnvData)
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