Essays about: "datorseende"

Showing result 31 - 35 of 407 essays containing the word datorseende.

1. 31. Real-time uncertainty estimation for deep learning

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Árni Dagur Guðmundsson; [2023]
   Keywords : Machine Learning; Deep Learning; Uncertainty Estimation; Evidential Deep Learning; Computer Vision; Maskininlärning; Djupinlärning; Osäkerhetsuppskattning; Evidential Deep Learning; Datorseende; Vélnám; Djúptauganet; Óvissumat; Evidential Deep Learning; Tölvusjón;

   Abstract : Modern deep neural networks do not produce well calibrated estimates of their own uncertainty, unless specific uncertainty estimation techniques are applied. Common uncertainty estimation techniques such as Deep Ensembles and Monte Carlo Dropout necessitate multiple forward pass evaluations for each input sample, making them too slow for real-time use. READ MORE

3. 32. Real-time Unsupervised Domain Adaptation

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Marc Botet Colomer; [2023]
   Keywords : Unsupervised Domain Adaptation; Real-Time applications; Online Learning; Self-Learning; Semantic Segmentation; Reinforcement Learning; Oövervakad domänanpassning; Realtidsapplikationer; Onlineinlärning; Självinlärning; Semantisk Segmentering; Förstärkningsinlärning;

   Abstract : 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 and safety in diverse and dynamic environments. READ MORE

4. 33. Meta-Pseudo Labelled Multi-View 3D Shape Recognition

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Fehmi Ayberk Uçkun; [2023]
   Keywords : 3D shape recognition; 3D object classification; 3D shape retrieval; 3D object retrieval; Automatic labelling; Semi-supervised learning; Pseudo labelling; Meta Pseudo Labelling; Multi-View Convolutional Neural Networks; Shape descriptors; Multi-view representations; Deeplearning; 3D-formigenkänning; 3D-objektklassificering; 3D-formhämtning; Hämtning av 3D-objekt; Automatisk märkning; Halv-vägledd lärning; Pseudomärkning; Meta Pseudo-märkning; Multi-View Faltningsnät; Formbeskrivningar; Multi-view representation; Djupinlärning;

   Abstract : The field of computer vision has long pursued the challenge of understanding the three-dimensional world. This endeavour is further fuelled by the increasing demand for technologies that rely on accurate perception of the 3D environment such as autonomous driving and augmented reality. READ MORE

5. 34. Automatic Detection of Structural Deformations in Batteries from Imaging data using Machine Learning : Exploring the potential of different approaches for efficient structural deformation detection

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Maira Khan; [2023]
   Keywords : CT scan; electrode peaks; jelly roll; keypoints; structural deformation; traditional computer vision; deep neural network; CT-skanning; elektrodtoppar; gelérulle; nyckelpunkter; strukturell deformation; Traditionellt datorseende; djupt neuralt nätverk;

   Abstract : The increasing occurrence of structural deformations in the electrodes of the jelly roll has raised quality concerns during battery manufacturing, emphasizing the need to detect them automatically with the advanced techniques. This thesis aims to explore and provide two models based on traditional computer vision (CV) and deep neural network (DNN) techniques using computed tomography (CT) scan images of jelly rolls to ensure that the product is of high quality. READ MORE

6. 35. Applicability of Detection Transformers in Resource-Constrained Environments : Investigating Detection Transformer Performance Under Computational Limitations and Scarcity of Annotated Data

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Altan Senel; [2023]
   Keywords : Deep Learning; Computer Vision; Self-supervised Learning; Object Detection; Scene Graph Generation;

   Abstract : Object detection is a fundamental task in computer vision, with significant applications in various domains. However, the reliance on large-scale annotated data and computational resource demands poses challenges in practical implementation. READ MORE