Rasmus N. Jørgensen
According to our database1, Rasmus N. Jørgensen authored at least 25 papers between 2013 and 2019.
Legend:Book In proceedings Article PhD thesis Other
A Novel Spatio-Temporal FCN-LSTM Network for Recognizing Various Crop Types Using Multi-Temporal Radar Images.
Remote Sensing, 2019
Disentangling Information in Artificial Images of Plant Seedlings Using Semi-Supervised GAN.
Remote Sensing, 2019
Preprocessed Sentinel-1 Data via a Web Service Focused on Agricultural Field Monitoring.
IEEE Access, 2019
The GrassClover Image Dataset for Semantic and Hierarchical Species Understanding in Agriculture.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019
Weed Growth Stage Estimator Using Deep Convolutional Neural Networks.
A Novel Locating System for Cereal Plant Stem Emerging Points' Detection Using a Convolutional Neural Network.
Multi-Modal Detection and Mapping of Static and Dynamic Obstacles in Agriculture for Process Evaluation.
Front. Robotics and AI, 2018
Current potentials and challenges using Sentinel-1 for broadacre field remote sensing.
Ground vehicle mapping of fields using LiDAR to enable prediction of crop biomass.
Robotic design choice overview using co-simulation.
Collaborative model based design of automated and robotic agricultural vehicles in the Crescendo Tool.
Estimation of the Botanical Composition of Clover-Grass Leys from RGB Images Using Data Simulation and Fully Convolutional Neural Networks.
FieldSAFE: Dataset for Obstacle Detection in Agriculture.
Designing and Testing a UAV Mapping System for Agricultural Field Surveying.
Preliminary Results of Clover and Grass Coverage and Total Dry Matter Estimation in Clover-Grass Crops Using Image Analysis.
J. Imaging, 2017
A Public Image Database for Benchmark of Plant Seedling Classification Algorithms.
Dicotyledon Weed Quantification Algorithm for Selective Herbicide Application in Maize Crops.
DeepAnomaly: Combining Background Subtraction and Deep Learning for Detecting Obstacles and Anomalies in an Agricultural Field.
Using Deep Learning to Challenge Safety Standard for Highly Autonomous Machines in Agriculture.
J. Imaging, 2016
Stereo and Active-Sensor Data Fusion for Improved Stereo Block Matching.
Proceedings of the Image Analysis and Recognition - 13th International Conference, 2016
Robotic Design Choice Overview Using Co-Simulation and Design Space Exploration.
Object Detection and Terrain Classification in Agricultural Fields Using 3D Lidar Data.
Proceedings of the Computer Vision Systems - 10th International Conference, 2015
Automated Detection and Recognition of Wildlife Using Thermal Cameras.
Towards an Open Software Platform for Field Robots in Precision Agriculture.
Seedling Discrimination with Shape Features Derived from a Distance Transform.