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Plankton recognition from imaging flow cytometer data using convolutional neural networks
(2018)
Research on plankton populations is bottlenecked by the ability to obtain species-level information within a required time frame. Recent technological advances in imaging hardware have made it possible to obtain large ...
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 ...
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 ...
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 ...
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 ...
Determination of resolution, repeatability, and detection capability improvements of automatic optical inspection in micro-electro-mechanical systems manufacturing
(2022)
Automatic optical inspection (AOI) is a quality monitoring system used in many industries. In semiconductor industry, it is used to detect anomalies, inter alia, defects in wafers and micro-electro-mechanical systems (MEMS). ...