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.
Monitoring of Varroa Infestation Rate in Beehives: A Simple AI ApproachL Picek, A Novozamsky, RC Frydrychova, B Zitova, P MachIEEEICIP | 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 placein the ImageCLEFdrawnUIChallenge. [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]