Search Results - "KARSTOFT, Henrik"

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  1. 1

    Embryo selection with artificial intelligence: how to evaluate and compare methods? by Kragh, Mikkel Fly, Karstoft, Henrik

    “…Embryo selection within in vitro fertilization (IVF) is the process of evaluating qualities of fertilized oocytes (embryos) and selecting the best embryo(s)…”
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  2. 2

    Plant species classification using deep convolutional neural network by Dyrmann, Mads, Karstoft, Henrik, Midtiby, Henrik Skov

    Published in Biosystems engineering (01-11-2016)
    “…Information on which weed species are present within agricultural fields is important for site specific weed management. This paper presents a method that is…”
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  3. 3

    Forecasting large-scale circulation regimes using deformable convolutional neural networks and global spatiotemporal climate data by Nielsen, Andreas Holm, Iosifidis, Alexandros, Karstoft, Henrik

    Published in Scientific reports (19-05-2022)
    “…Classifying the state of the atmosphere into a finite number of large-scale circulation regimes is a popular way of investigating teleconnections, the…”
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  4. 4

    Automatic grading of human blastocysts from time-lapse imaging by Kragh, Mikkel F., Rimestad, Jens, Berntsen, Jørgen, Karstoft, Henrik

    Published in Computers in biology and medicine (01-12-2019)
    “…Blastocyst morphology is a predictive marker for implantation success of in vitro fertilized human embryos. Morphology grading is therefore commonly used to…”
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  5. 5

    Object Detection of Small Insects in Time-Lapse Camera Recordings by Bjerge, Kim, Frigaard, Carsten Eie, Karstoft, Henrik

    Published in Sensors (Basel, Switzerland) (01-08-2023)
    “…As pollinators, insects play a crucial role in ecosystem management and world food production. However, insect populations are declining, necessitating…”
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  6. 6

    DeepAnomaly: Combining Background Subtraction and Deep Learning for Detecting Obstacles and Anomalies in an Agricultural Field by Christiansen, Peter, Nielsen, Lars N, Steen, Kim A, Jørgensen, Rasmus N, Karstoft, Henrik

    Published in Sensors (Basel, Switzerland) (11-11-2016)
    “…Convolutional neural network (CNN)-based systems are increasingly used in autonomous vehicles for detecting obstacles. CNN-based object detection and per-pixel…”
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  7. 7

    CloudCast: A Satellite-Based Dataset and Baseline for Forecasting Clouds by Nielsen, Andreas Holm, Iosifidis, Alexandros, Karstoft, Henrik

    “…Forecasting the formation and development of clouds is a central element of modern weather forecasting systems. Incorrect cloud forecasts can lead to major…”
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  8. 8

    Development of a real-time computer vision system for tracking loose-housed pigs by Ahrendt, Peter, Gregersen, Torben, Karstoft, Henrik

    Published in Computers and electronics in agriculture (01-05-2011)
    “…► Development of a camera based computer vision system for tracking the loose housed pigs. ► The advantage of the solution is that it is not necessary to mount…”
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  9. 9

    FieldSAFE: Dataset for Obstacle Detection in Agriculture by Kragh, Mikkel Fly, Christiansen, Peter, Laursen, Morten Stigaard, Larsen, Morten, Steen, Kim Arild, Green, Ole, Karstoft, Henrik, Jørgensen, Rasmus Nyholm

    Published in Sensors (Basel, Switzerland) (09-11-2017)
    “…In this paper, we present a multi-modal dataset for obstacle detection in agriculture. The dataset comprises approximately 2 h of raw sensor data from a…”
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  10. 10

    Automated detection and recognition of wildlife using thermal cameras by Christiansen, Peter, Steen, Kim Arild, Jørgensen, Rasmus Nyholm, Karstoft, Henrik

    Published in Sensors (Basel, Switzerland) (30-07-2014)
    “…In agricultural mowing operations, thousands of animals are injured or killed each year, due to the increased working widths and speeds of agricultural…”
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  11. 11

    A deep learning pipeline for time-lapse camera monitoring of insects and their floral environments by Bjerge, Kim, Karstoft, Henrik, Mann, Hjalte M.R., Høye, Toke T.

    Published in Ecological informatics (01-12-2024)
    “…Arthropods, including insects, represent the most diverse group and contribute significantly to animal biomass. Automatic monitoring of insects and other…”
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  12. 12

    Weed Classification Using Explainable Multi-Resolution Slot Attention by Farkhani, Sadaf, Skovsen, Søren Kelstrup, Dyrmann, Mads, Jørgensen, Rasmus Nyholm, Karstoft, Henrik

    Published in Sensors (Basel, Switzerland) (09-10-2021)
    “…In agriculture, explainable deep neural networks (DNNs) can be used to pinpoint the discriminative part of weeds for an imagery classification task, albeit at…”
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  13. 13

    Estimation of the Botanical Composition of Clover-Grass Leys from RGB Images Using Data Simulation and Fully Convolutional Neural Networks by Skovsen, Søren, Dyrmann, Mads, Mortensen, Anders Krogh, Steen, Kim Arild, Green, Ole, Eriksen, Jørgen, Gislum, René, Jørgensen, Rasmus Nyholm, Karstoft, Henrik

    Published in Sensors (Basel, Switzerland) (17-12-2017)
    “…Optimal fertilization of clover-grass fields relies on knowledge of the clover and grass fractions. This study shows how knowledge can be obtained by analyzing…”
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  14. 14

    Robust Species Distribution Mapping of Crop Mixtures Using Color Images and Convolutional Neural Networks by Skovsen, Søren Kelstrup, Laursen, Morten Stigaard, Kristensen, Rebekka Kjeldgaard, Rasmussen, Jim, Dyrmann, Mads, Eriksen, Jørgen, Gislum, René, Jørgensen, Rasmus Nyholm, Karstoft, Henrik

    Published in Sensors (Basel, Switzerland) (29-12-2020)
    “…Crop mixtures are often beneficial in crop rotations to enhance resource utilization and yield stability. While targeted management, dependent on the local…”
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  15. 15

    Illumination and Reflectance Estimation with its Application in Foreground Detection by Tu, Gang Jun, Karstoft, Henrik, Pedersen, Lene Juul, Jørgensen, Erik

    Published in Sensors (Basel, Switzerland) (28-08-2015)
    “…In this paper, we introduce a novel approach to estimate the illumination and reflectance of an image. The approach is based on illumination-reflectance model…”
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  16. 16

    Disentangling Information in Artificial Images of Plant Seedlings Using Semi-Supervised GAN by Madsen, Simon Leminen, Mortensen, Anders Krogh, Jørgensen, Rasmus Nyholm, Karstoft, Henrik

    Published in Remote sensing (Basel, Switzerland) (01-11-2019)
    “…Lack of annotated data for training of deep learning systems is a challenge for many visual recognition tasks. This is especially true for domain-specific…”
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  17. 17

    Comparison of 10 Perfusion MRI Parameters in 97 Sub-6-Hour Stroke Patients Using Voxel-Based Receiver Operating Characteristics Analysis by CHRISTENSEN, Søren, MOURIDSEN, Kim, WU, Ona, HJORT, Niels, KARSTOFT, Henrik, THOMALLA, Götz, RÖTHER, Joachim, FIEHLER, Jens, KUCINSKI, Thomas, STERGAARD, Leif Ø

    Published in Stroke (1970) (01-06-2009)
    “…Perfusion-weighted imaging can predict infarct growth in acute stroke and potentially be used to select patients with tissue at risk for reperfusion therapies…”
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  18. 18

    Improvement of KinectTM sensor capabilities by fusion with laser sensing data using octree by Chávez, Alfredo, Karstoft, Henrik

    Published in Sensors (Basel, Switzerland) (01-04-2012)
    “…To enhance sensor capabilities, sensor data readings from different modalities must be fused. The main contribution of this paper is to present a sensor data…”
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  19. 19

    Multi-Modal Detection and Mapping of Static and Dynamic Obstacles in Agriculture for Process Evaluation by Korthals, Timo, Kragh, Mikkel, Christiansen, Peter, Karstoft, Henrik, Jørgensen, Rasmus N, Rückert, Ulrich

    Published in Frontiers in robotics and AI (27-03-2018)
    “…Today, agricultural vehicles are available that can automatically perform tasks such as weed detection and spraying, mowing, and sowing while being steered…”
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  20. 20

    Detection of bird nests during mechanical weeding by incremental background modeling and visual saliency by Steen, Kim Arild, Therkildsen, Ole Roland, Green, Ole, Karstoft, Henrik

    Published in Sensors (Basel, Switzerland) (02-03-2015)
    “…Mechanical weeding is an important tool in organic farming. However, the use of mechanical weeding in conventional agriculture is increasing, due to public…”
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