Publications

Investigating the influence of hyperspectral data compression on spectral unmixing
Kuester, J.; Anastasiadis, J.; Middelmann, W.; Heizmann, M.
2022. Image and Signal Processing for Remote Sensing XXVIII. Ed.: L. Bruzzone, Art.: 122670H-1–11, SPIE. doi:10.1117/12.2636129 

GAN-regularized augmentation strategy for spectral datasets [GAN-regularisierte Augmentierungsstrategie für spektrale Datensätze]
Anastasiadis, J.; Heizmann, M.
2022. Technisches Messen, 89 (4), 278–288. doi:10.1515/teme-2021-0109 

Gaussian Process Inspired Neural Networks for Spectral Unmixing Dataset Augmentation
Anastasiadis, J.; Heizmann, M.
2021. Artificial Intelligence. Ed.: K.-H. Schäfer, 61–70, Hochschule Kaiserslautern 

Generation of artificial training data for spectral unmixing by modelling spectral variability using Gaussian random variables
Anastasiadis, J.; Heizmann, M.
2021. OCM 2021 - Optical Characterization of Materials : Conference Proceedings. Ed.: J. Beyerer; T. Längle, 129–139, Karlsruher Institut für Technologie (KIT) 

CNN-based augmentation strategy for spectral unmixing datasets considering spectral variability
Anastasiadis, J.; Heizmann, M.
2020. SPIE REMOTE SENSING - Image and Signal Processing for Remote Sensing XXVI, 21-25 September 2020. Ed.: L. Bruzzone, 188 – 199, SPIE. doi:10.1117/12.2575875 

Erzeugung künstlicher Datensätze zum Training konvolutionaler neuronaler Netze für die spektrale Entmischung
Anastasiadis, J.; Benzing, P.; Puente León, F.
2020. Technisches Messen, 87 (9), 542–552. doi:10.1515/teme-2020-0008 

Ortsaufgelöste spektrale Entmischung mit Hilfe von konvolutionalen neuronalen Netzen / Spatially resolved spectral unmixing using convolutional neural networks
Anastasiadis, J.; Puente León, F.
2019. Technisches Messen, 86 (s1), 122–126. doi:10.1515/teme-2019-0062 

Robust iterative estimation of material abundances based on spectral filters exploiting the SVD
Krippner, W.; Anastasiadis, J.; Puente Léon, F.
2019. Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imaging XXVI, 26-30 April 2020, Anaheim Convention Center, Anaheim, California, United States, Art.-Nr.: 109861T, Society of Photo-optical Instrumentation Engineers (SPIE). doi:10.1117/12.2518195

Spatially resolved ingredient detection in spice mixes using 3D convolutional neural networks
Anastasiadis, J.; Krippner, W.; Puente Léon, F.
2019. OCM 2019 - Optical Characterization of Materials : Conference Proceedings. Ed.: J. Beyerer; F. Puente León, T. Längle, 35–44, KIT Scientific Publishing. doi:10.5445/IR/1000092319 

Detektion von Stoffen in Lebensmitteln mit Hilfe von 3D-Faltungsautoencodern = Detection of substances in food with 3D convolutional autoencoders
Anastasiadis, J.; Puente León, F.
2018. Technisches Messen, 85 (s1), s38–s44. doi:10.1515/teme-2018-0033 

Identification and sorting of regular textures according to their similarity
Hernández Mesa, P.; Anastasiadis, J.; Puente León, F.
2015. Automated Visual Inspection and Machine Vision : 24 June 2015, Munich, Germany. Ed.: J. Beyerer, 95300A, Society of Photo-optical Instrumentation Engineers (SPIE). doi:10.1117/12.2184439