This map shows the geographic impact of K. Nowakowski's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by K. Nowakowski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites K. Nowakowski more than expected).
This network shows the impact of papers produced by K. Nowakowski. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by K. Nowakowski. The network helps show where K. Nowakowski may publish in the future.
Co-authorship network of co-authors of K. Nowakowski
This figure shows the co-authorship network connecting the top 25 collaborators of K. Nowakowski.
A scholar is included among the top collaborators of K. Nowakowski based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with K. Nowakowski. K. Nowakowski is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Weres, J., et al.. (2013). Semantic web technologies for enhancing web-based decision support system for designing and managing drying and storage of cereal grains.. Journal of Research and Applications in Agricultural Engineering. 58(2). 184–187.1 indexed citations
Nowakowski, K., et al.. (2011). Image analysis and neural networks in the process of identifying of selected mechanical damage to maize caryopses.. Journal of Research and Applications in Agricultural Engineering. 56(1). 100–102.2 indexed citations
Boniecki, P., et al.. (2009). Neural image data compression in the process of identification of selected agricultural objects.. Journal of Research and Applications in Agricultural Engineering. 54(2). 19–23.
13.
Nowakowski, K., P. Boniecki, & Jacek Dach. (2009). Neural image analysis in identification process of mechanical damages of kernels.. Journal of Research and Applications in Agricultural Engineering. 54(2). 77–80.
14.
Boniecki, P. & K. Nowakowski. (2008). Classification of maize's kernels with supporting neuronal identification of shape. Journal of Research and Applications in Agricultural Engineering.2 indexed citations
15.
Nowakowski, K. & P. Boniecki. (2008). Wpływ liczby zmiennych na jakość działania neuronowego modelu do identyfikacji mechanicznych uszkodzeń ziarniaków kukurydzy. Agricultural Engineering/Inżynieria Rolnicza. 151–157.2 indexed citations
16.
Nowakowski, K. & P. Boniecki. (2008). Neuronowy model do identyfikacji makrouszkodzeń ziarniaków. Journal of Research and Applications in Agricultural Engineering. 53. 79–81.1 indexed citations
17.
Boniecki, P. & K. Nowakowski. (2008). Klasyfikacja ziarniaków kukurydzy w oparciu o neuronową identyfikację kształtu. Journal of Research and Applications in Agricultural Engineering. 53. 14–17.
18.
Nowakowski, K., et al.. (2007). Wybór reprezentatywnej struktury zbiorów uczących dla potrzeb neuronowych modeli identyfikacyjnych wykorzystywanych w inżynierii rolniczej. Agricultural Engineering/Inżynieria Rolnicza. 183–188.1 indexed citations
19.
Nowakowski, K., et al.. (2007). Przetwarzanie graficznych danych empirycznych dla potrzeb edukacji sztucznych sieci neuronowych, modelujących wybrane zagadnienia inżynierii rolniczej. Agricultural Engineering/Inżynieria Rolnicza. 243–248.2 indexed citations
20.
Mueller, W., P. Boniecki, J. Weres, & K. Nowakowski. (2007). Modelowanie danych w procesie odwzorowywania informatycznego systemów empirycznych stanowiących przedmiot inżynierii rolniczej. Agricultural Engineering/Inżynieria Rolnicza. 175–182.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.