@article{SteinertStabernack2022,
  author    = {Steinert, Fritjof and Stabernack, Benno},
  title     = {Architecture of a low latency H.264/AVC video codec for robust ML based image classification how region of interests can minimize the impact of coding artifacts},
  series = {Journal of Signal Processing Systems for Signal, Image, and Video Technology},
  volume    = {94},
  journal   = {Journal of Signal Processing Systems for Signal, Image, and Video Technology},
  number    = {7},
  publisher = {Springer},
  address   = {New York},
  issn      = {1939-8018},
  doi       = {10.1007/s11265-021-01727-2},
  pages     = {693 -- 708},
  year      = {2022},
  abstract  = {The use of neural networks is considered as the state of the art in the field of image classification. A large number of different networks are available for this purpose, which, appropriately trained, permit a high level of classification accuracy. Typically, these networks are applied to uncompressed image data, since a corresponding training was also carried out using image data of similar high quality. However, if image data contains image errors, the classification accuracy deteriorates drastically. This applies in particular to coding artifacts which occur due to image and video compression. Typical application scenarios for video compression are narrowband transmission channels for which video coding is required but a subsequent classification is to be carried out on the receiver side. In this paper we present a special H.264/Advanced Video Codec (AVC) based video codec that allows certain regions of a picture to be coded with near constant picture quality in order to allow a reliable classification using neural networks, whereas the remaining image will be coded using constant bit rate. We have combined this feature with the ability to run with lowest latency properties, which is usually also required in remote control applications scenarios. The codec has been implemented as a fully hardwired High Definition video capable hardware architecture which is suitable for Field Programmable Gate Arrays.},
  language  = {en}
}
@article{SysłoKwiatkowska2015,
  author    = {Sysło, Maciej M. and Kwiatkowska, Anna Beata},
  title     = {Think logarithmically!},
  series = {KEYCIT 2014 - Key Competencies in Informatics and ICT},
  journal   = {KEYCIT 2014 - Key Competencies in Informatics and ICT},
  number    = {7},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  issn      = {1868-0844},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-82923},
  pages     = {371 -- 380},
  year      = {2015},
  abstract  = {We discuss here a number of algorithmic topics which we use in our teaching and in learning of mathematics and informatics to illustrate and document the power of logarithm in designing very efficient algorithms and computations - logarithmic thinking is one of the most important key competencies for solving real world practical problems. We demonstrate also how to introduce logarithm independently of mathematical formalism using a conceptual model for reducing a problem size by at least half. It is quite surprising that the idea, which leads to logarithm, is present in Euclid's algorithm described almost 2000 years before John Napier invented logarithm.},
  language  = {en}
}
@article{TavakoliAlirezazadehHedayatipouretal.2021,
  author    = {Tavakoli, Hamad and Alirezazadeh, Pendar and Hedayatipour, Ava and Nasib, A. H. Banijamali and Landwehr, Niels},
  title     = {Leaf image-based classification of some common bean cultivars using discriminative convolutional neural networks},
  series = {Computers and electronics in agriculture : COMPAG online ; an international journal},
  volume    = {181},
  journal   = {Computers and electronics in agriculture : COMPAG online ; an international journal},
  publisher = {Elsevier},
  address   = {Amsterdam [u.a.]},
  issn      = {0168-1699},
  doi       = {10.1016/j.compag.2020.105935},
  pages     = {11},
  year      = {2021},
  abstract  = {In recent years, many efforts have been made to apply image processing techniques for plant leaf identification. However, categorizing leaf images at the cultivar/variety level, because of the very low inter-class variability, is still a challenging task. In this research, we propose an automatic discriminative method based on convolutional neural networks (CNNs) for classifying 12 different cultivars of common beans that belong to three various species. We show that employing advanced loss functions, such as Additive Angular Margin Loss and Large Margin Cosine Loss, instead of the standard softmax loss function for the classification can yield better discrimination between classes and thereby mitigate the problem of low inter-class variability. The method was evaluated by classifying species (level I), cultivars from the same species (level II), and cultivars from different species (level III), based on images from the leaf foreside and backside. The results indicate that the performance of the classification algorithm on the leaf backside image dataset is superior. The maximum mean classification accuracies of 95.86, 91.37 and 86.87\% were obtained at the levels I, II and III, respectively. The proposed method outperforms the previous relevant works and provides a reliable approach for plant cultivars identification.},
  language  = {en}
}
@article{Teske2014,
  author    = {Teske, Daniel},
  title     = {Geocoder accuracy ranking},
  series = {Process design for natural scientists: an agile model-driven approach},
  journal   = {Process design for natural scientists: an agile model-driven approach},
  number    = {500},
  publisher = {Springer},
  address   = {Berlin},
  isbn      = {978-3-662-45005-5},
  issn      = {1865-0929},
  pages     = {161 -- 174},
  year      = {2014},
  abstract  = {Finding an address on a map is sometimes tricky: the chosen map application may be unfamiliar with the enclosed region. There are several geocoders on the market, they have different databases and algorithms to compute the query. Consequently, the geocoding results differ in their quality. Fortunately the geocoders provide a rich set of metadata. The workflow described in this paper compares this metadata with the aim to find out which geocoder is offering the best-fitting coordinate for a given address.},
  language  = {en}
}
@article{Vierheller2014,
  author    = {Vierheller, Janine},
  title     = {Exploratory Data Analysis},
  series = {Process Design for Natural Scientists: an agile model-driven approach},
  journal   = {Process Design for Natural Scientists: an agile model-driven approach},
  number    = {500},
  editor    = {Lambrecht, Anna-Lena and Margaria, Tiziana},
  publisher = {Axel Springer Verlag},
  address   = {Berlin},
  isbn      = {978-3-662-45005-5},
  issn      = {1865-0929},
  pages     = {110 -- 126},
  year      = {2014},
  abstract  = {In bioinformatics the term exploratory data analysis refers to different methods to get an overview of large biological data sets. Hence, it helps to create a framework for further analysis and hypothesis testing. The workflow facilitates this first important step of the data analysis created by high-throughput technologies. The results are different plots showing the structure of the measurements. The goal of the workflow is the automatization of the exploratory data analysis, but also the flexibility should be guaranteed. The basic tool is the free software R.},
  language  = {en}
}
@article{Webb2015,
  author    = {Webb, Mary},
  title     = {Considerations for the Design of Computing Curricula},
  series = {KEYCIT 2014 - Key Competencies in Informatics and ICT},
  journal   = {KEYCIT 2014 - Key Competencies in Informatics and ICT},
  number    = {7},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  issn      = {1868-0844},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-82723},
  pages     = {267 -- 283},
  year      = {2015},
  abstract  = {This paper originated from discussions about the need for important changes in the curriculum for Computing including two focus group meetings at IFIP conferences over the last two years. The paper examines how recent developments in curriculum, together with insights from curriculum thinking in other subject areas, especially mathematics and science, can inform curriculum design for Computing. The analysis presented in the paper provides insights into the complexity of curriculum design as well as identifying important constraints and considerations for the ongoing development of a vision and framework for a Computing curriculum.},
  language  = {en}
}
@article{WegnerZenderLucke2015,
  author    = {Wegner, Christian and Zender, Raphael and Lucke, Ulrike},
  title     = {ProtoSense},
  series = {KEYCIT 2014 - Key Competencies in Informatics and ICT},
  journal   = {KEYCIT 2014 - Key Competencies in Informatics and ICT},
  number    = {7},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  issn      = {1868-0844},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-82970},
  pages     = {405 -- 407},
  year      = {2015},
  language  = {en}
}
@article{Weigend2015,
  author    = {Weigend, Michael},
  title     = {How Things Work},
  series = {KEYCIT 2014 - Key Competencies in Informatics and ICT},
  journal   = {KEYCIT 2014 - Key Competencies in Informatics and ICT},
  number    = {7},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  issn      = {1868-0844},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-82814},
  pages     = {285 -- 298},
  year      = {2015},
  abstract  = {Recognizing and defining functionality is a key competence adopted in all kinds of programming projects. This study investigates how far students without specific informatics training are able to identify and verbalize functions and parameters. It presents observations from classroom activities on functional modeling in high school chemistry lessons with altogether 154 students. Finally it discusses the potential of functional modelling to improve the comprehension of scientific content.},
  language  = {en}
}
@article{ZierisGerstbergerMueller2015,
  author    = {Zieris, Holger and Gerstberger, Herbert and M{\"u}ller, Wolfgang},
  title     = {Using Arduino-Based Experiments to Integrate Computer Science Education and Natural Science},
  series = {KEYCIT 2014 - Key Competencies in Informatics and ICT},
  journal   = {KEYCIT 2014 - Key Competencies in Informatics and ICT},
  number    = {7},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  issn      = {1868-0844},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-82938},
  pages     = {381 -- 389},
  year      = {2015},
  abstract  = {Current curricular trends require teachers in Baden- Wuerttemberg (Germany) to integrate Computer Science (CS) into traditional subjects, such as Physical Science. However, concrete guidelines are missing. To fill this gap, we outline an approach where a microcontroller is used to perform and evaluate measurements in the Physical Science classroom. Using the open-source Arduino platform, we expect students to acquire and develop both CS and Physical Science competencies by using a self-programmed microcontroller. In addition to this combined development of competencies in Physical Science and CS, the subject matter will be embedded in suitable contexts and learning environments, such as weather and climate.},
  language  = {en}
}