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20212026
most citedMachine Learning and Computer Vision Techniques in Continuous Beehive Monitoring Applications: A survey

4 citations · 4 across the 4 of their papers we have counts for

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cs.CV2026

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…

cs.CV2024

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…

cs.CV2024

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…

cs.CV2022★ 4 cited

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…

cs.CV2021

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…