Development and validation of deep learning based embryo selection across multiple days of transfer

no code implementations • 5 Oct 2022 • Jacob Theilgaard Lassen, Mikkel Fly Kragh, Jens Rimestad, Martin Nygård Johansen, Jørgen Berntsen

This work describes the development and validation of a fully automated deep learning model, iDAScore v2. 0, for the evaluation of embryos incubated for 2, 3, and 5 or more days.

Robust and generalizable embryo selection based on artificial intelligence and time-lapse image sequences

no code implementations • 12 Mar 2021 • Jørgen Berntsen, Jens Rimestad, Jacob Theilgaard Lassen, Dang Tran, Mikkel Fly Kragh

However, as of now, only limited research has been conducted to evaluate how embryo selection models generalize to new clinics and how they perform in subgroup analyses across various conditions.

UnsuperPoint: End-to-end Unsupervised Interest Point Detector and Descriptor

2 code implementations • 9 Jul 2019 • Peter Hviid Christiansen, Mikkel Fly Kragh, Yury Brodskiy, Henrik Karstoft

In this work, we introduce an unsupervised deep learning-based interest point detector and descriptor.

Homography Estimation

FieldSAFE: Dataset for Obstacle Detection in Agriculture

1 code implementation • 11 Sep 2017 • Mikkel Fly Kragh, Peter Christiansen, Morten Stigaard Laursen, Morten Larsen, Kim Arild Steen, Ole Green, Henrik Karstoft, Rasmus Nyholm Jørgensen

In this paper, we present a novel multi-modal dataset for obstacle detection in agriculture.

Robotics