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Smart grasping of known objects
(2020)
Smart grasping means that a robot can automatically decide which object and how an object can be grasped. Firstly, a neural network should find the objects and get a 2D bounding box. The convolution neural network is used ...
3D reconstruction of logs from board images
(2022)
Sawmills nowadays are heavily automated and especially sawing process optimisation could improve overall yield of sawn timber. The main focus of this thesis work is to create a method to reconstruct a 3D-model of a log ...
Human-in-the-loop for efficient training of retinal image analysis methods
(2021)
Eye-related diseases like diabetic retinopathy can be visually diagnosed by medical experts. However, this is time-consuming work requires much effort. For solving this problem, automated computer-aided solutions have been ...
Deep learning for point cloud segmentation with applications to sawmill industry
(2022)
Nowadays, the integration of digital technologies in enterprises is happening everywhere. The sawmill industry is no exception. The various stages of production at sawmills are being improved through the use of information ...
Estimating glue-layer defects on plywood through computer vision methods
(2023)
Making quality film-faced plywood is a vital issue for the manufacturer as it decides the quality of the end product made from this film-faced plywood. Detecting defects on the applied glue which is used to stick the films ...
Human micro-gesture recognition by adversarial training
(2023)
Human communication is based on primarily on verbal language, that is complex enough to deliver deep concepts, but alongside that, non-verbal language delivers other kinds of details, like intentional and non-intentional ...
Face anti-spoofing by using diffusion model
(2024)
This thesis explores the potential of diffusion models for improving face anti-spoofing (FAS) techniques. Due to the increasing usage of facial recognition systems in various domains, such as smartphone unlocking, airport ...