Search for dissertations about: "unsupervised machine learning"

Showing result 1 - 5 of 58 swedish dissertations containing the words unsupervised machine learning.

2. 1. Visual Analytics for Explainable and Trustworthy Machine Learning

   Author : Angelos Chatzimparmpas; Andreas Kerren; Rafael M. Martins; Ilir Jusufi; Alex Endert; Linnéuniversitetet; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; visualization; interaction; visual analytics; explainable machine learning; XAI; trustworthy machine learning; ensemble learning; dimensionality reduction; supervised learning; unsupervised learning; ML; AI; tabular data; visualisering; interaktion; visuell analys; förklarlig maskininlärning; XAI; pålitlig maskininlärning; ensembleinlärning; dimensionesreducering; övervakad inlärning; oövervakad inlärning; ML; AI; tabelldata; Computer Science; Datavetenskap; Informations- och programvisualisering; Information and software visualization;

   Abstract : The deployment of artificial intelligence solutions and machine learning research has exploded in popularity in recent years, with numerous types of models proposed to interpret and predict patterns and trends in data from diverse disciplines. However, as the complexity of these models grows, it becomes increasingly difficult for users to evaluate and rely on the model results, since their inner workings are mostly hidden in black boxes, which are difficult to trust in critical decision-making scenarios. READ MORE

4. 2. Towards Digitization and Machine learning Automation for Cyber-Physical System of Systems

   Author : Saleha Javed; Marcus Liwicki; Fredrik Sandin; Hamam Mokayed; Luleå tekniska universitet; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; Digitization; Automation; Industry 4.0; Machine-to-Machine Translation; Ontology Alignment Eclipse Arrowhead Framework; Machine Learning; Unsupervised Learning; Condition Monitoring; Ontology Alignment; Cyber-Physical Systems; Cyberfysiska system;

   Abstract : Cyber-physical systems (CPS) connect the physical and digital domains and are often realized as spatially distributed. CPS is built on the Internet of Things (IoT) and Internet of Services, which use cloud architecture to link a swarm of devices over a decentralized network. Modern CPSs are undergoing a foundational shift as Industry 4. READ MORE

5. 3. Advanced Machine Learning Methods for Oncological Image Analysis

   Author : Mehdi Astaraki; Chunliang Wang; Örjan Smedby; Iuliana Toma-Dasu; Bjoern Menze; KTH; Karolinska Institutet; Karolinska Institutet; []
   Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Medical Image Analysis; Machine Learning; Deep Learning; Survival Analysis; Early Response Assessment; Tumor Classification; Tumor Segmentation; Medicinsk teknologi; Medical Technology;

   Abstract : Cancer is a major public health problem, accounting for an estimated 10 million deaths worldwide in 2020 alone. Rapid advances in the field of image acquisition and hardware development over the past three decades have resulted in the development of modern medical imaging modalities that can capture high-resolution anatomical, physiological, functional, and metabolic quantitative information from cancerous organs. READ MORE

6. 4. Self-supervised Representation Learning for Visual Domains Beyond Natural Scenes

   Author : Prakash Chandra Chhipa; Marcus Liwicki; Seiichi Uchida; Rajkumar Saini; Josep Lladós; Luleå tekniska universitet; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; self-supervised learning; representation learning; computer vision; learning with few labels; Maskininlärning; Machine Learning;

   Abstract : This thesis investigates the possibility of efficiently adapting self-supervised representation learning on visual domains beyond natural scenes, e.g., medical imagining and non-RGB sensory images. READ MORE

7. 5. Manifold Learning in Computational Biology

   Author : Jens Nilsson; Matematik LTH; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; Nonlinear Dimensionality Reduction; Gene Expression Data; Computational Biology; Machine Learning; Manifold Learning;

   Abstract : This thesis deals with manifold learning techniques and their application in gene expression data analysis. Manifold learning is the study of methods that aim to infer geometrical structure from data sampled from manifolds, enabling nonlinear solutions to various machine learning tasks. READ MORE