no code implementations • 21 Mar 2024 • Zina-Sabrina Duma, Tomas Zemcik, Simon Bilik, Tuomas Sihvonen, Peter Honec, Satu-Pia Reinikainen, Karel Horak
Hyperspectral (HS) imagery in agriculture is becoming increasingly common.
no code implementations • 27 Apr 2023 • Jakub Nevlacil, Simon Bilik, Karel Horak
A declining honeybee population could pose a threat to a food resources of the whole world one of the latest trend in beekeeping is an effort to monitor a health of the honeybees using various sensors and devices.
1 code implementation • 27 Apr 2023 • Juraj Lagin, Simon Bilik
In this paper we present a method to analyze the inner structure of the composite FRP rebar, namely the shift of the real center of gravity with a respect to the geometrical center of rebar and changes of cross-sectional characteristics.
no code implementations • 15 Mar 2023 • Simon Bilik, Daniel Batrakhanov, Tuomas Eerola, Lumi Haraguchi, Kaisa Kraft, Silke Van den Wyngaert, Jonna Kangas, Conny Sjöqvist, Karin Madsen, Lasse Lensu, Heikki Kälviäinen, Karel Horak
Thus, we propose an unsupervised anomaly detection system based on the similarity of the original and autoencoder-reconstructed samples.
no code implementations • 29 Jul 2022 • Simon Bilik, Tomas Zemcik, Lukas Kratochvila, Dominik Ricanek, Milos Richter, Sebastian Zambanini, Karel Horak
Wide use and availability of the machine learning and computer vision techniques allows development of relatively complex monitoring systems in many domains.
1 code implementation • 24 Mar 2022 • Simon Bilik, Karel Horak
In this paper, we suggest a way, how to use SIFT and SURF algorithms to extract the image features for anomaly detection.
1 code implementation • 13 Mar 2022 • Simon Bilik, Karel Horak
We show that the convolutional autoencoder architecture doesn't have a significant effect for this task and we prove the potential of our approach on the real world dataset.
no code implementations • 26 Feb 2021 • Simon Bilik, Lukas Kratochvila, Adam Ligocki, Ondrej Bostik, Tomas Zemcik, Matous Hybl, Karel Horak, Ludek Zalud
Here we present an object detector based method for health state monitoring of bee colonies.