59 citations · 70 across the 9 of their papers we have counts for
9 papers
Towards automatic smoke detector inspection: Recognition of the smoke detectors in industrial facilities and preparation for future drone integration
Lukas Kratochvila, Jakub Stefansky, Simon Bilik +6
Fire safety consists of a complex pipeline, and it is a very important topic of concern. One of its frontal parts are the smoke detectors, which are supposed to provide an alarm pr…
Recognizing and Reconstructing a Multi-Unit Floor Plan
Lukas Kratochvila, Gijs de Jong, Monique Arkesteijn +4
Digital twins have a major potential to form a significant part of urban management in emergency planning, as they allow more efficient designing of the escape routes, better orien…
Computer Vision Approaches for Automated Bee Counting Application
Simon Bilik, Ilona Janakova, Adam Ligocki +2
Many application from the bee colony health state monitoring could be efficiently solved using a computer vision techniques. One of such challenges is an efficient way for counting…
Varroa destructor detection on honey bees using hyperspectral imagery
Zina-Sabrina Duma, Tomas Zemcik, Simon Bilik +4
Hyperspectral (HS) imagery in agriculture is becoming increasingly common. These images have the advantage of higher spectral resolution. Advanced spectral processing techniques ar…
Raspberry Pi Bee Health Monitoring Device
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 u…
Machine Learning and Computer Vision Techniques in Continuous Beehive Monitoring Applications: A survey
Simon Bilik, Tomas Zemcik, Lukas Kratochvila +4
Wide use and availability of the machine learning and computer vision techniques allows development of relatively complex monitoring systems in many domains. Besides the traditiona…
Feature space reduction as data preprocessing for the anomaly detection
Simon Bilik, Karel Horak
In this paper, we present two pipelines in order to reduce the feature space for anomaly detection using the One Class SVM. As a first stage of both pipelines, we compare the perfo…
SIFT and SURF based feature extraction for the anomaly detection
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. We use those feature vectors to train various classifiers…
Visual diagnosis of the Varroa destructor parasitic mite in honeybees using object detector techniques
Simon Bilik, Lukas Kratochvila, Adam Ligocki +5
The Varroa destructor mite is one of the most dangerous Honey Bee (Apis mellifera) parasites worldwide and the bee colonies have to be regularly monitored in order to control its s…