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Detection of Mechanical Damages in Sawn Timber Using Convolutional Neural Networks
(Springer, Cham, 2019-02-14)
The quality control of timber products is vital for the sawmill industry pursuing more efficient production processes. This paper considers the automatic detection of mechanical damages in wooden board surfaces occurred ...
Fine-Grained Wood Species Identification Using Convolutional Neural Networks
(Springer, Cham, 2019-05-12)
This paper considers the wood species identification from images of boards. The identification using only visual features of the surface is a challenging task even for an expert. The task becomes especially difficult when ...
3D Hand Movement Measurement Framework for Studying Human-Computer Interaction
(Springer, Cham, 2019-12-30)
In order to develop better touch and gesture user interfaces, it is important to be able to measure how humans move their hands while interacting with technical devices. The recent advances in high-speed imaging technology ...
Plankton Recognition in Images with Varying Size
(Springer, Cham, 2021-02-25)
Monitoring plankton is important as they are an essential part of the aquatic food web as well as producers of oxygen. Modern imaging devices produce a massive amount of plankton image data which calls for automatic ...
On De-Interlacing and Sub-Pixel Precision Tracking
(IEEE, 2021-12-29)
Video cameras with interlaced scan sensors find applications in a variety of tasks such as object tracking due to their lower overhead in terms of memory and the higher sensitivity in comparison to their counterparts that ...
Timber Tracing with Multimodal Encoder-Decoder Networks
(Springer, Cham, 2019-08-22)
Tracking timber in the sawmill environment from the raw material (logs) to the end product (boards) provides various benefits including efficient process control, the optimization of sawing, and the prediction of end-product ...
Open-Set Plankton Recognition Using Similarity Learning
(Springer, Cham, 2022-12-11)
Automatic plankton recognition provides new possibilities to study plankton populations and various environmental aspects related to them. Most of the existing recognition methods focus on individual datasets with a known ...