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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, ...
Hand tracking with sub-pixel precision
(2020)
Human-Computer Interaction has matured from simple keyboard and mouse interface to touch screens, and more recently to 3-D touch screen interfaces. Recently, high precision object tracking algorithms are being deployed for ...
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 ...
Metric learning based pattern matching for species agnostic animal re-identification
(2021)
In the active effort to monitor and protect endangered animal species, modern technology is replacing the previously used conventional techniques of tracking using GPS or tagging which are considered invasive in nature. ...
Plankton recognition using similarity learning
(2021)
Several automated classification methods for plankton images have been developed. These methods typically require an explicit description of features, data augmentation, and are not suitable for classes with a few example ...
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 ...
Image clustering for unsupervised analysis of plankton data
(2020)
Advancements in automated imaging has made it possible to enhance the data both in terms of quantity and quality. This has prompted the development of plankton imaging systems for acquiring the species level information ...
End-to-end regression of clinical parameters from retinal images
(2020)
Retinal images are widely used by medical doctors to diagnose eye-related diseases. Unfortunately, the human factor restricts possibilities of full analysis of fundus. Therefore, implementing an automated algorithm for ...
Instance segmentation of Ladoga ringed seals
(2020)
The wildlife photo-identification is an important issue today since it allows to identify and to track animals. It helps scientists to monitor the endangered species, although it is difficult to explore all the image ...
Improving the performance of Bayesian deep model training for artery-vein segmentation
(2020)
Retinal images are an important tool for diagnosis of ocular diseases. Automating the process of screening the retinal images would allow wider screening and make diagnosing of patients’ swifter. The possibility of performing ...