34 citations · 57 across the 16 of their papers we have counts for
17 papers
Unsupervised Pelage Pattern Unwrapping for Animal Re-identification
Aleksandr Algasov, Ekaterina Nepovinnykh, Fedor Zolotarev +4
Existing individual re-identification methods often struggle with the deformable nature of animal fur or skin patterns which undergo geometric distortions due to body movement and…
Multimodal surface defect detection from wooden logs for sawing optimization
Bořek Reich, Matej Kunda, Fedor Zolotarev +3
We propose a novel, good-quality, and less demanding method for detecting knots on the surface of wooden logs using multimodal data fusion. Knots are a primary factor affecting the…
Towards synthetic generation of realistic wooden logs
Fedor Zolotarev, Borek Reich, Tuomas Eerola +2
In this work, we propose a novel method to synthetically generate realistic 3D representations of wooden logs. Efficient sawmilling heavily relies on accurate measurement of logs a…
Deep Unsupervised Segmentation of Log Point Clouds
Fedor Zolotarev, Tuomas Eerola, Tomi Kauppi
In sawmills, it is essential to accurately measure the raw material, i.e. wooden logs, to optimise the sawing process. Earlier studies have shown that accurate predictions of the i…
Open-Set Plankton Recognition
Joona Kareinen, Annaliina Skyttä, Tuomas Eerola +5
This paper considers open-set recognition (OSR) of plankton images. Plankton include a diverse range of microscopic aquatic organisms that have an important role in marine ecosyste…
Mineral segmentation using electron microscope images and spectral sampling through multimodal graph neural networks
Samuel Repka, Bořek Reich, Fedor Zolotarev +2
We propose a novel Graph Neural Network-based method for segmentation based on data fusion of multimodal Scanning Electron Microscope (SEM) images. In most cases, Backscattered Ele…
Self-Supervised Pretraining for Fine-Grained Plankton Recognition
Joona Kareinen, Tuomas Eerola, Kaisa Kraft +3
Plankton recognition is an important computer vision problem due to plankton's essential role in ocean food webs and carbon capture, highlighting the need for species-level monitor…
Understanding the Impact of Training Set Size on Animal Re-identification
Aleksandr Algasov, Ekaterina Nepovinnykh, Tuomas Eerola +4
Recent advancements in the automatic re-identification of animal individuals from images have opened up new possibilities for studying wildlife through camera traps and citizen sci…
DAPlankton: Benchmark Dataset for Multi-instrument Plankton Recognition via Fine-grained Domain Adaptation
Daniel Batrakhanov, Tuomas Eerola, Kaisa Kraft +6
Plankton recognition provides novel possibilities to study various environmental aspects and an interesting real-world context to develop domain adaptation (DA) methods. Different…
Combining feature aggregation and geometric similarity for re-identification of patterned animals
Veikka Immonen, Ekaterina Nepovinnykh, Tuomas Eerola +2
Image-based re-identification of animal individuals allows gathering of information such as migration patterns of the animals over time. This, together with large image volumes col…
Survey of Automatic Plankton Image Recognition: Challenges, Existing Solutions and Future Perspectives
Tuomas Eerola, Daniel Batrakhanov, Nastaran Vatankhah Barazandeh +7
Planktonic organisms are key components of aquatic ecosystems and respond quickly to changes in the environment, therefore their monitoring is vital to understand the changes in th…
Towards Phytoplankton Parasite Detection Using Autoencoders
Simon Bilik, Daniel Batrakhanov, Tuomas Eerola +9
Phytoplankton parasites are largely understudied microbial components with a potentially significant ecological impact on phytoplankton bloom dynamics. To better understand their i…
NORPPA: NOvel Ringed seal re-identification by Pelage Pattern Aggregation
Ekaterina Nepovinnykh, Ilia Chelak, Tuomas Eerola +1
We propose a method for Saimaa ringed seal (Pusa hispida saimensis) re-identification. Access to large image volumes through camera trapping and crowdsourcing provides novel possib…
SealID: Saimaa ringed seal re-identification dataset
Ekaterina Nepovinnykh, Tuomas Eerola, Vincent Biard +4
Wildlife camera traps and crowd-sourced image material provide novel possibilities to monitor endangered animal species. However, massive image volumes that these methods produce a…
EDEN: Deep Feature Distribution Pooling for Saimaa Ringed Seals Pattern Matching
Ilia Chelak, Ekaterina Nepovinnykh, Tuomas Eerola +2
In this paper, pelage pattern matching is considered to solve the individual re-identification of the Saimaa ringed seals. Animal re-identification together with the access to larg…
Resolving Overlapping Convex Objects in Silhouette Images by Concavity Analysis and Gaussian Process
Sahar Zafari, Mariia Murashkina, Tuomas Eerola +3
Segmentation of overlapping convex objects has various applications, for example, in nanoparticles and cell imaging. Often the segmentation method has to rely purely on edges betwe…
Semantic Computing of Moods Based on Tags in Social Media of Music
Pasi Saari, Tuomas Eerola
Social tags inherent in online music services such as Last.fm provide a rich source of information on musical moods. The abundance of social tags makes this data highly beneficial…