Lukáš Picek

University of West BohemiaFaculty of Applied SciencesCzechia


NTIS, Technická 8, 301 00 PilsenRoom UN525 | Map


Danish Svampe Atlas (Lead Investigator)

  • Developing Rest API service for automatic fungi recognition.
  • Fine-tuning of the lightweight MobileNet-V3 custom architecture.
  • In close cooperation with Czech Technical University, Danish Mycological Society, and Google.
  • iOS App | Android App | Web App | Models | Publications: 1, 2, 3

Snake Species Recognition (Lead Investigator)

  • A platform for fast and reliable snake species recognition using AI and herpetologists..Developing REST API service and Web Application for automatic snake species recognition. Curatingnovel open-source benchmark dataset and organizing ML competitions
  • In close cooperation with Florida Gulf Coast University, University of Geneva, Instutute of Global Health, Médecins Sans Frontières and many more.
  • About Project | Demo App | Publications: 1

Varroa Destructor Detection (Lead Investigator)

  • Developing Rest API service for automatic Varroa destructor detection
  • In cooperation with Czech Academy of Sciences, and IBM
  • About Project | Publications: 1

Carnivore ID (Lead Investigator)

  • Research & Development in the topic of Lynx identification.
  • In close cooperation with Mendel University in Brno, Bavarian Forest National Park, Leibniz-Institute for Zoo and Wildlife Research and many others.
  • About Project

DiDYMOS - Dynamic digital street model for the usage of autonomous mobility in Pilsen

  • Automatic Data extraction for digital street model tailored for autonomous trams
  • In cooperation with Škoda Transportation, Škoda Digital, CEDA Maps, INTENS Corporation, and ČVUT
  • About Project

Selected Publications

Monitoring of Varroa Infestation Rate in Beehives: A Simple AI ApproachL Picek, A Novozamsky, RC Frydrychova, B Zitova, P MachIEEE ICIP | 2022 | URL
An artificial intelligence model to identify snakes from across the world: Opportunities and challenges for global health and herpetologyI Bolon, L Picek, AM Durso, G Alcoba, F Chappuis, R Ruiz de CastañedaPLOS - Neglected Tropical Diseases | 2022 | URL
Danish fungi 2020 — Not just another image recognition datasetPicek, L., Šulc, M., Matas, J., Jeppesen, T. S., Heilmann-Clausen, J., Læssøe, T., & Frøslev, T.CVF WACV | 2022 | URL
Automatic Fungi Recognition: Deep Learning Meets MycologyL Picek, M Šulc, J Matas, J Heilmann-Clausen, TS Jeppesen, E LindMDPI SENSORS | 2022 | URL
Plant recognition by AI: Deep neural nets, transformers, and kNN in deep embeddingsL Picek, M Šulc, Y Patel, J MatasFrontiers in Plant Science | 2022 | URL
Fungi Recognition: A Practical Use CaseM. Šulc, L. Picek, J. Matas, T. Jeppesen, J. Heilmann-ClausenCVF WACV | 2020 | URL
Recognition of the Amazonian Flora by Inception Networks with Test-time Class Prior EstimationL. Picek, M. Šulc, J. MatasCLEF | 2019 | URL
Plant Recognition by Inception Networks with Test-time Class Prior EstimationM. Šulc, L. Picek, J. MatasCLEF | 2018 | URL
Coral Reef Annotation, Localisation and Pixel-wise Classification using Mask-RCNN and Bag of TricksL.Picek, A. Říha, A. ZitaCLEF | 2020 | URL
Mastering Large Scale Multi-label Image Recognition with high efficiency over Camera trap imagesM. Valan, L. PicekCVPR - FGVCW | 2020 | URL

Competitions & Challenges

  • 1st place in the ImageCLEFdrawnUI Challenge. [2021]
  • 1st place in the Crop Disease recognition - ICLR Computer Vision for Agriculture Workshop. [2020]
  • 1st place in the Hakuna Ma-Data recognition challenge sponsored by Microsoft AI for Earth [2020]
  • 1st place in the ImageCLEFcoral Challenge. [2020]
  • 1st place in the ImageCLEFdrawnUI Challenge. [2020]
  • 1st place in the FGVCx Flower Classification and FGVCx Fungi Classification. [2019]
  • 2nd place in the FGVCx iDesigner. [2019]


  • [ENG] - Meet the winners of the HaKuna Ma-Data challenge - URL
  • [ENG] - Doctors Without Borders to field test Czech researcher’s snakebite app - URL
  • [ENG] - Google AI Blog Announcing the 7th Fine-Grained Visual Categorization Workshop - URL
  • [CZ] - Čeští vědci vyvinuli software pro mobilní aplikaci, která rozeznává houby - URL
  • [CZ] - Student ZČU v Plzni Lukáš Picek sklízí mezinárodní úspěchy - URL
  • [CZ] - Česká umělá inteligence pozná houby stejně dobře jako nejlepší experti - URL