Sebastian Haug

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In this paper we propose a benchmark dataset for crop / weed discrimination, single plant phenotyping and other open computer vision tasks in precision agriculture. The dataset comprises 60 images with annotations and is available online. All images were acquired with the autonomous field robot Bonirob in an organic carrot farm while the carrot plants were(More)
This paper proposes a machine vision approach for plant classification without segmentation and its application in agriculture. Our system can discriminate crop and weed plants growing in commercial fields where crop and weed grow close together and handles overlap between plants. Automated crop / weed discrimination enables weed control strategies with(More)
In this system paper we present a novel approach for autonomous, mobile manipulation for agricultural robots. Our target application is mechanical weed control which for example is needed in organic farming. Today, this task is often performed by field workers, whose availability is declining and the quality of their work differs greatly. In addition,(More)
A digital bandpass delta-sigma modulator for class-S power amplifiers is presented. In comparison to a 2-level modulator coding efficiency can be increased by 10% over a large input power range with a 3-level modulator. Scaling the quantizer thresholds offers a trade-off between coding efficiency and signal-to-noise ratio. The bandpass modulator(More)
The collaborative research project RemoteFarming.1 integrates innovative agricultural engineering (field robotics, sensors, actuators) and web-based communication technologies. It aims to develop a robotic weed control system which integrates a human user as remote worker in the process. Thus, it drastically reduces the complexity of the problem in(More)
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