Iskanje po katalogu digitalne knjižnice

Opis: Well-being is essential for pupils’ academic and personal growth. Since schools are central to children’s lives, they must provide a safe environment that supports emotional needs. This study explores how primary school teachers use transitional objects and rituals that help children adapt to school and feel secure. Findings reveal that teachers employ these tools intuitively, often without theoretical grounding. Despite their informal use, these practices positively influence pupils’ adaptation and the classroom climate. The study underscores the importance of integrating transitional elements into educational practice and calls for enhanced teacher training focused on emotional well-being and its role in early education.
Ključne besede: primary education, well-being, transitional object, transitional ritual, transient object
Objavljeno v DKUM: 15.12.2025; Ogledov: 0; Prenosov: 0
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Opis: This study focuses on the segmentation part in the development of a potato-sorting system that utilizes camera input for the segmentation and classification of potatoes. The key challenge addressed is the need for efficient segmentation to allow the sorter to handle a higher volume of potatoes simultaneously. To achieve this, the study employs a region-based convolutional neural network (R-CNN) approach for the segmentation task, while trying to achieve more precise segmentation than with classic CNN-based object detectors. Specifically, Mask R-CNN is implemented and evaluated based on its performance with different parameters in order to achieve the best segmentation results. The implementation and methodologies used are thoroughly detailed in this work. The findings reveal that Mask R-CNN models can be utilized in the production process of potato sorting and can improve the process.
Ključne besede: image segmentation, potato sorting, neural network, mask RCNN, object detection, production process, machine learning, AI
Objavljeno v DKUM: 27.03.2025; Ogledov: 0; Prenosov: 24
Celotno besedilo (5,97 MB)
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Opis: The goal of this study was to develop an automated monitoring system for the detection of pigs’ bodies, heads and tails. The aim in the first part of the study was to recognize individual pigs (in lying and standing positions) in groups and their body parts (head/ears, and tail) by using machine learning algorithms (feature pyramid network). In the second part of the study, the goal was to improve the detection of tail posture (tail straight and curled) during activity (standing/moving around) by the use of neural network analysis (YOLOv4). Our dataset (n = 583 images, 7579 pig posture) was annotated in Labelbox from 2D video recordings of groups (n = 12–15) of weaned pigs. The model recognized each individual pig’s body with a precision of 96% related to threshold intersection over union (IoU), whilst the precision for tails was 77% and for heads this was 66%, thereby already achieving human-level precision. The precision of pig detection in groups was the highest, while head and tail detection precision were lower. As the first study was relatively time-consuming, in the second part of the study, we performed a YOLOv4 neural network analysis using 30 annotated images of our dataset for detecting straight and curled tails. With this model, we were able to recognize tail postures with a high level of precision (90%).
Ključne besede: pig, welfare, image processing, object detection, deep learning, smart farming
Objavljeno v DKUM: 11.07.2024; Ogledov: 87; Prenosov: 10
Celotno besedilo (48,11 MB)
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Opis: This thesis aims to implement an open-source framework for the automatic alignment and tracking of the KORUZA v2 Pro free-space optical solution. Free-space optical systems are explored and current optical alignment and tracking solutions are analyzed. We use Neural Network-based object detection approaches to complement the essential collection of framework functionality. We train a Neural Network to detect KORUZA v2 Pro units with data gathered from currently deployed links. The out-of-the-box solution for automatic alignment and tracking can be freely modified and extended.
Ključne besede: free-space optics, automatic alignment, neural networks, object detection, open-source framework
Objavljeno v DKUM: 14.03.2022; Ogledov: 801; Prenosov: 99
Celotno besedilo (4,68 MB)

Opis: Modelling is a crucial tool in research and development, but models simplify oneʼs perception of systems as mental pictures of reality, maybe too much. Therefore one must be aware of the addressed relations, typology of models, and apply 'USOMID - 6 Thinking Hats' method of creative cooperation to attain requisite holism of approach and requisite wholeness of outcomes.
Ključne besede: object, system, dialectical system, model, USOMID, 6 thinking hats
Objavljeno v DKUM: 10.07.2015; Ogledov: 1626; Prenosov: 419
Celotno besedilo (212,77 KB)
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