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Presence of alien Prunus serotina and Impatiens parviflora in lowland forest fragments in NE Slovenia
Mirjana Šipek, Eva Horvat, Ivana Vitasović Kosić, Nina Šajna, 2022, izvirni znanstveni članek

Opis: Temperate alluvial, riparian and lowland forests are the European forests with the greatest presence of invasive alien plants. Consequently, identifying the environmental conditions for and other drivers behind the establishment of invasive species in natural forest communities is crucial for understanding the invasibility of these habitats. We focused on fragments (patches) of Illyrian oak-hornbeam forest in NE Slovenia, which are the least studied in this regard. Because alien phanerophytes and therophytes are significantly over-represented compared to native plantsin lowland forests, we selected two representative invasives: the phanerophyte Prunus serotina and the therophyte Impatiens parviflora. By using logistic regression models on vegetation surveys, environmental data based on Ellenberg´s indicator values, and patch metrics, we identified patch characteristics explaining the presence of each species. Moreover, we included human impact in the models. We reveal significant characteristics differentiating P. serotina from I. parviflora. We also show that the perimeterarea ratio and soil nutrients of the forest patches correlate significantly with the presence of P. serotina, while human disturbance correlates significantly with the presence of I. parviflora. Our results and a similar approach for other invasive plant species can be applied to assess habitat invasibility on potential and species’ current geographic distribution, as well as to develop management plans.
Ključne besede: biological invasions, forest fragmentation, landscape metrics, habitat characteristics, human presence, anthropogenic factors, neophytes, Slovenia
Objavljeno v DKUM: 12.07.2024; Ogledov: 136; Prenosov: 11
Celotno besedilo (460,99 KB)
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ARM-Based Video Intercom System with Next-Gen Human Presence Detection using Deep Learning : magistrsko delo
Mario Gavran, 2022, magistrsko delo

Opis: This master's thesis presents an advanced video system with human presence detection based on deep learning and an ARM microcontroller. The objective of the thesis is to develop a system that works as a smart video intercom, which could be installed, e.g. on the entrance door, and autonomously alert the owner that a guest is in front of the door. The main goal is to use an AI algorithm, namely the neural network model on a constrained device, such as an ARM microcontroller, as their main advantage is lower power consumption and cost. The thesis also describes commonly used methods to reduce the power and memory footprint and to implement and accelerate the deep learning algorithms more effectively. Further, the most notable deep learning hardware and some general platforms are described in more detail. The thesis also presents the development of a human presence detection system based on an ARM microcontroller, VGA camera, and LCD, where Tensorflow Lite Micro, an open-source C++ framework for deploying deep learning models to embedded platforms and a pre-trained neural network model for person presence detection are used.
Ključne besede: TensorFlow Lite Micro, Video intercom system, ARM Cortex-M microcontroller, Human presence detection, Neural network
Objavljeno v DKUM: 08.07.2022; Ogledov: 783; Prenosov: 55
Celotno besedilo (7,86 MB)

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