Zobrazeno 1 - 10
of 46
pro vyhledávání: '"semantisk segmentering"'
Autor:
G Sneltvedt, Isak
Replicating a real-world environment is crucial for creating simulations, computer vision, global and local path planning, and localization. While computer-aided design software is a standard tool for such a task, it may not always be practical or ef
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-344752
Autor:
Wang, Xinchen
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 it
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-344750
Autor:
William Coble, Kyle
This thesis addresses the problem of improving the delineation of skylines, also referred to as skyline detection, in occluded and challenging environments where existing skyline delineation methods may struggle or fail. Delineated skylines can be us
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-335106
Autor:
Morales Brotons, Daniel
Learning from unlabeled data is a topic of critical significance in machine learning, as the large datasets required to train ever-growing models are costly and impractical to annotate. Semi-Supervised Learning (SSL) methods aim to learn from a few l
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-334680
Autor:
Westphal, Ronny
This study details the development of a neural network model designed for real-time semantic segmentation, specifically to distinguish sky pixels from other elements within an image. The model is incorporated into a feature for an Augmented Reality a
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-336885
Autor:
Botet Colomer, Marc
Machine learning systems have been demonstrated to be highly effective in various fields, such as in vision tasks for autonomous driving. However, the deployment of these systems poses a significant challenge in terms of ensuring their reliability an
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-326113
Autor:
Sanchez Nieto, Juan
Reducing the size of a neural network whilst maintaining a comparable performance is an important problem to be solved since the constrictions on resources of small devices make it impossible to deploy large models in numerous real-life scenarios. A
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-325107
Autor:
Panagiotakopoulos, Theodoros
Deep Learning models have seen great application in demanding tasks such as machine translation and autonomous driving. However, building such models has proved challenging, both from a computational perspective and due to the requirement of a pletho
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-309749
Autor:
Rengarajan, Sri Janani
Quantization of Neural Networks is popular technique for adopting computation intensive Deep Learning applications to edge devices. In this work, low bit mixed precision quantization of FPN-Resnet18 model trained for the task of semantic segmentation
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-312264
Autor:
Melki, Jakob
This project is about screw hole detection using neural networks for automated assembly and disassembly. In a lot of industrial companies, such as Ericsson AB, there are products such as radio units or filters that have a lot of screw holes. Thus, th
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-308443