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Andreas Backhaus

Andreas Backhaus
Ingenieurbüro Dr. Andreas Backhaus

PhD
Freelance Machine Learning Engineer

About

39
Publications
5,432
Reads
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471
Citations

Publications

Publications (39)
Article
Biofortification, the enrichment of nutrients in crop plants, is of increasing importance to improve human health. The wild barley nested association mapping (NAM) population HEB-25 was developed to improve agronomic traits including nutrient concentration. Here, we evaluated the potential of high-throughput hyperspectral imaging in HEB-25 to predi...
Conference Paper
Full-text available
Using previously generated machine learning models under changing sensor hardware with nearly the same performance is a desirable goal. This constitutes a model transfer problem. We compare a Radial Basis Function Network adapted for transfer learning to a classical data alignment approach. This approach to transfer machine-learning models is teste...
Article
Hyperspectral sensor systems play a key role in the automation of work processes in the farming industry. Non-invasive measurements of plants allow for an assessment of the vitality and health state and can also be used to classify weeds or infected parts of a plant. However, one major downside of hyperspectral cameras is that they are not very cos...
Chapter
Full-text available
Information processing systems with some form of machine-learned component are making their way into the industrial application and offer high potentials for increasing productivity and machine utilization. However, the systematic engineering approach to integrate and manage these machine-learned components is still not standardized and no referenc...
Article
Full-text available
Grapevine yellows (GY) are serious phytoplasma-caused diseases affecting viticultural areas worldwide. At present, two principal agents of GY are known to infest grapevines in Germany: Bois noir (BN) and Palatinate grapevine yellows (PGY). Disease management is mostly based on prophylactic measures as there are no curative in-field treatments avail...
Article
Full-text available
Background Grapevine trunk diseases (GTDs) such as Esca are among the most devastating threats to viticulture. Due to the lack of efficient preventive and curative treatments, Esca causes severe economic losses worldwide. Since symptoms do not develop consecutively, the true incidence of the disease in a vineyard is difficult to assess. Therefore,...
Article
Full-text available
Grapevine leafroll disease (GLD) is considered one of the most widespread grapevine virus diseases, causing severe economic losses worldwide. To date, six grapevine leafroll-associated viruses (GLRaVs) are known as causal agents of the disease, of which GLRaV-1 and-3 induce the strongest symptoms. Due to the lack of efficient curative treatments in...
Preprint
Full-text available
Background: Grapevine trunk diseases (GTDs) such as Esca are among the most devastating threats to viticulture. Due to the lack of efficient preventive and curative treatments, Esca causes severe economic losses worldwide. Since symptoms do not develop consecutively, the true incidence of the disease in a vineyard is difficult to assess. Therefore,...
Preprint
Full-text available
Plant diseases, as one of the perpetual problems in agriculture, is increasingly difficult to manage due to intensifying of the field production, global trafficking, reduction of genetic variability of crops, climatic changes-driven expansion of pests, redraw and loss of effectiveness of pesticides and rapid breakdown of the disease resistance in t...
Article
Full-text available
Hyperspectral imaging enables researchers and plant breeders to analyze various traits of interest like nutritional value in high throughput. In order to achieve this, the optimal design of a reliable calibration model, linking the measured spectra with the investigated traits, is necessary. In the present study we investigated the impact of differ...
Article
Full-text available
Enhancing the accumulation of essential mineral elements in cereal grains is of prime importance for combating human malnutrition. Biofortification by breeding holds great potential for improving nutrient accumulation in grains. However, conventional breeding approaches require element analysis of many grain samples, which causes high costs. Here w...
Article
Phosphorus (P) is an important macronutrient required for plant growth and yield formation. Since decades, breeders aim to optimize P efficiency in crops. We studied a set of 47 wild barley (Hordeum vulgare ssp. spontaneum, Hsp) introgression lines (ILs) in hydroponic culture to identify quantitative trait loci (QTLs) improving growth and nutrient...
Article
Full-text available
In grapevine research the acquisition of phenotypic data is largely restricted to the field due to its perennial nature and size. The methodologies used to assess morphological traits and phenology are mainly limited to visual scoring. Some measurements for biotic and abiotic stress, as well as for quality assessments, are done by invasive measures...
Article
Full-text available
Cercospora beticola is an economically significant fungal pathogen of sugar beet, and is the causative pathogen of Cercospora leaf spot. Selected host genotypes with contrasting degree of susceptibility to the disease have been exploited to characterize the patterns of metabolite responses to fungal infection, and to devise a pre-symptomatic, non-i...
Article
Full-text available
We present a new characterization technique based on hyperspectral imaging applied to silicon wafers. It combines the measurement of spatially and spectrally resolved reflection features and a dedicated subsequent data analysis. This method allows for a rapid localization and classification of defects and contaminations on wafers. Thus, it compleme...
Conference Paper
Training and application of prototype based learning approaches such as Learning Vector Quantization, Radial Basis Function networks, and Supervised Neural Gas require the use of distance metrics to measure the similarities between feature vectors as well as class prototypes. While the Euclidean distance is used in many cases, the highly correlated...
Article
Against the background of classification in data mining tasks typically various aspects of accuracy, and often also of model size are considered so far. The aspect of interpretability is just beginning to gain general attention. This paper evaluates all three of these aspects within the context of several computational intelligence based paradigms...
Article
Ensembles of RBF networks trained with \(\gamma\)-divergence-based similarity measures can improve classification accuracy of hyperspectral imaging data significantly compared to any single RBF network as well as to RBF ensembles based on the Euclidian distance. So far, the drawback of using classifier ensembles is the need to compute the results o...
Conference Paper
Full-text available
Classically, machine learning methods are evaluated according to their accuracy and model size. Increasingly model parameters are used to interpret the model in order to extract information about the data it was build on. The capability of a model to deliver this kind of information, its interpretability, is so far more or less subjective. In this...
Conference Paper
Full-text available
Hyperspectral imaging has been proven to be a viable tool for automated food inspection that is non-invasive and on-line capable. In this contribution a hardware implemented Self-Organizing Feature Map with Conscience (C-SOM) is presented that is capable of on-line adaptation and recall in order to learn to classify green coffee varieties as well a...
Conference Paper
We propose relevance learning for unsupervised online vector quantization algorithm based on stochastic gradient descent learning according to the given vector quantization cost function. We consider several widely used models including the neural gas algorithm, the Heskes variant of self-organizing maps and the fuzzy c-means. We apply the relevan...
Conference Paper
Full-text available
Hyperspectral imaging of crop plants offers the means for a non-invasive, precise and high-throughput plant-phenotyping in plant research and precision agriculture. We already reported the successful separation of spectral signatures by means of unsupervised learning (e.g. clustering) of tobacco leaves grown from different genetic background and un...
Conference Paper
In this paper we investigate the use of multivariate multiresolution principal component analysis for filtering and denoising of signals. From the proposed model we deduce several properties that particularly address the properties of hyper-spectral image data. We thereby aim at overcoming shortcomings of other methods close to the approach specifi...
Article
Full-text available
Understanding the relationship of the size and shape of an organism to the size, shape, and number of its constituent cells is a basic problem in biology; however, numerous studies indicate that the relationship is complex and often nonintuitive. To investigate this problem, we used a system for the inducible expression of genes involved in the G1/...
Article
Full-text available
In earlier work, we developed the Selective Attention for Identification Model (SAIM [16]). SAIM models the human ability to perform translation-invariant object identification in multiple object scenes. SAIM suggests that central for this ability is an interaction between parallel competitive processes in a selection stage and a object identificat...
Article
Full-text available
*Significant progress has been made in the identification of the genetic factors controlling leaf shape. However, no integrated solution for the quantification and categorization of leaf form has been developed. In particular, the analysis of local changes in margin growth, which define many of the differences in shape, remains problematical. *Here...
Conference Paper
The assessment of visible differences in leaf shape between plant species or mutants (phenotyping) plays a significant role in plant research. This paper investigates the application of unsupervised data clustering techniques for phenotype screening to find hidden common shape categories. A set of two wildtypes and seven mutations of Arabidopsis ac...
Article
Full-text available
Expansins are cell wall proteins associated with the process of plant growth. However, investigations in which expansin gene expression has been manipulated throughout the plant have often led to inconclusive results. In this article, we report on a series of experiments in which overexpression of expansin was targeted to specific phases of leaf gr...
Conference Paper
Full-text available
We recently presented a computational model of object recognition and attention: the Selective Attention for Identification model (SAIM) [1,2,3,4,5,6,7]. SAIM was developed to model normal attention and attentional disorders by implementing translation-invariant object recognition in multiple object scenes. SAIM can simulate a wide range of experim...
Conference Paper
Full-text available
Visual search is a commonly-used paradigm in psychological studies of attention. It is well-known that search efficiency is influenced by a broad range of factors, e.g. the featural similarity between targets and distractors [4] or the featural configuration (see [16] for a review). Recently, a series of paper by Chun and colleagues (see [1] for a...
Conference Paper
Full-text available
It is a prerequisite for the successful application of service robots in human dominated domains to have intuitive and natural man-machine interfaces. In this context, it is desirable to extract information, such as the gender, age, or emotional state (via facial expressions) about the user to aid in communication. We developed a method to estimate...
Conference Paper
Full-text available
It is a prerequisite for the successful appli- cation of service robots in human dominated domains to have intuitive and natural man-machine-interfaces. In this context, it is desirable to extract information, such as the gender, age, or emotional state (via facial ex- pressions) about the user to aid in communication. We developed a method to esti...

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