Sebastian Haug

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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 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 3. All images were acquired with the autonomous field robot Bonirob in an organic carrot farm while the carrot plants(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)
Small size agricultural robots which are capable of sensing and manipulating the field environment are a promising approach towards more ecological, sustainable and human-friendly agriculture. This chapter proposes a machine vision approach for plant classification in the field and discusses its possible application in the context of robot based precision(More)
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