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Journal Articles
- 2021
[j3]Godliver Owomugisha
, Friedrich Melchert, Ernest Mwebaze, John A. Quinn, Michael Biehl:
Matrix Relevance Learning From Spectral Data for Diagnosing Cassava Diseases. IEEE Access 9: 83355-83363 (2021)- 2020
- [j2]Michiel Straat, Marika Kaden, Matthias Gay, Thomas Villmann, Alexander Lampe, Udo Seiffert, Michael Biehl, Friedrich Melchert:
Learning vector quantization and relevances in complex coefficient space. Neural Comput. Appl. 32(24): 18085-18099 (2020) - [j1]Friedrich Melchert, Gabriele Bani, Udo Seiffert, Michael Biehl:
Adaptive basis functions for prototype-based classification of functional data. Neural Comput. Appl. 32(24): 18213-18223 (2020)
Conference and Workshop Papers
- 2020
- [c5]Godliver Owomugisha, Pius K. B. Mugagga, Friedrich Melchert, Ernest Mwebaze, John A. Quinn, Michael Biehl:
A low-cost 3-D printed smartphone add-on spectrometer for diagnosis of crop diseases in field. COMPASS 2020: 331-332 - 2017
- [c4]Michiel Straat, Marika Kaden, Matthias Gay, Thomas Villmann, Alexander Lampe, Udo Seiffert, Michael Biehl, Friedrich Melchert:
Prototypes and matrix relevance learning in complex fourier space. WSOM 2017: 139-144 - [c3]Gabriele Bani, Udo Seiffert, Michael Biehl, Friedrich Melchert:
Adaptive basis functions for prototype-based classification of functional data. WSOM 2017: 145-152 - [c2]Marika Kaden, David Nebel, Friedrich Melchert, Andreas Backhaus, Udo Seiffert, Thomas Villmann:
Data dependent evaluation of dissimilarities in nearest prototype vector quantizers regarding their discriminating abilities. WSOM 2017: 220-226 - 2016
- [c1]Friedrich Melchert, Udo Seiffert, Michael Biehl:
Functional Representation of Prototypes in LVQ and Relevance Learning. WSOM 2016: 317-327
Coauthor Index
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