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Showing result 1 - 5 of 140 essays matching the above criteria.
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1. Exploring the Depth-Performance Trade-Off : Applying Torch Pruning to YOLOv8 Models for Semantic Segmentation Tasks
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : In order to comprehend the environments from different aspects, a large variety of computer vision methods are developed to detect objects, classify objects or even segment them semantically. Semantic segmentation is growing in significance due to its broad applications in fields such as robotics, environmental understanding for virtual or augmented reality, and autonomous driving. READ MORE
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2. Re-design and usability improvement of Arvue : an AR application displaying house models in their real context
University essay from Umeå universitet/Institutionen för tillämpad fysik och elektronikAbstract : Building your own house may be the biggest decision and greatest investment of your life, which calls for an informed decision regarding the house design. However, two-dimensional drawings may lack external context and might, for untrained eyes, not communicate how the house will look on its intended site. READ MORE
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3. Deep Learning-Based Depth Estimation Models with Monocular SLAM : Impacts of Pure Rotational Movements on Scale Drift and Robustness
University essay from Linköpings universitet/DatorseendeAbstract : This thesis explores the integration of deep learning-based depth estimation models with the ORB-SLAM3 framework to address challenges in monocular Simultaneous Localization and Mapping (SLAM), particularly focusing on pure rotational movements. The study investigates the viability of using pre-trained generic depth estimation networks, and hybrid combinations of these networks, to replace traditional depth sensors and improve scale accuracy in SLAM systems. READ MORE
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4. Enabling cyber-physical system for manufacturing systems using augmented reality
University essay from Högskolan i Skövde/Institutionen för ingenjörsvetenskapAbstract : This project focuses on addressing the challenges faced by manufacturing lines such as complexity and flexibility through the integration of Augmented Reality (AR), Internet of Things (IoT), and Big Data technologies. The objective is to develop a framework that enhances the efficiency, flexibility, and sustainability of manufacturing processes in the context of Industry 4. READ MORE
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5. Robust Background Segmentation For Use in Real-time Application : A study on using available foreground-background segmentation research for real-world application
University essay from Linköpings universitet/Institutionen för datavetenskapAbstract : In a world reliant on big industries to produce large quantities of more or less every product used, it is of utmost importance that the machines in such industries continue to run with minimum amounts of downtime. One way more and more providers of such industrial machines try to help their customers reduce downtime when a machine stops working or needs maintenance is through the use of remote guidance; a way of knowledge transfer from a technician to a regular employee that aims to allow the regular employee to be guided in real-time by a technician to solve the task himself, thus, not needing the technician to travel to the factory. READ MORE
