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Unsupervised anomaly detection from wooden boards using autoencoders
(2019)
For wood processing in the sawmill industry, quality of the raw material in every step affects the production efficiency. Defects in the sawn timber, such as wane, knots, cracks, watermarks, fungal damage, insect defects, ...
CNN-based ringed seal pelage pattern extraction
(2020)
The topic of this thesis is inspired by the conservation efforts of Saimaa ringed seals, which are in danger of becoming extinct with no appropriate actions. The work aims to develop a fur pattern extraction framework to ...
Virtual sawing using generative adversarial networks
(2021)
The global trend towards digitalization along with the 4th Industrial Revolution allows building new innovative solutions to optimize manufacturing. In particular, the highly competitive sawmill industry is not an exception. ...
Understanding multimodal timber matching networks via activation maps
(2021)
The use of digital technologies in timber tracing from the raw material to the end product, i.e., from logs to boards, provides benefits for the sawmilling industry such as better product quality prediction, efficient ...
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 ...