@article {fehr_12_bilder,
	title = {Bilder berechnen - nicht nur aufnehmen},
	journal = {Optik \& Photonik},
	volume = {7},
	year = {2012},
	pages = {50-53},
	doi = {10.1002/opph.201290021},
	author = {Fehr, J. and Bernd J{\"a}hne}
}
@article {fehr2012,
	title = {Bilder berechnen --- nicht nur aufnehmen : {\textquoteleft}{\textquoteleft}Computational Photography{\textquoteright}{\textquoteright} wird zunehmend interessant f{\"u}r die industrielle Bildverarbeitung},
	journal = {Optik \& Photonik},
	volume = {7},
	number = {1},
	year = {2012},
	pages = {50--53},
	doi = {10.1002/opph.201290021},
	author = {Fehr, Janis and Bernd J{\"a}hne}
}
@booklet {jaehne2011a,
	title = {Bringing the ocean inside the lab, image processing in environmental sciences},
	year = {2011},
	url = {www.laborundmore.de/},
	author = {Bernd J{\"a}hne}
}
@conference {hoernlein2009,
	title = {Boosting shift-invariant features},
	booktitle = {Pattern Recognition},
	volume = {5748},
	year = {2009},
	pages = {121--130},
	publisher = {Springer},
	organization = {Springer},
	abstract = {This work presents a novel method for training shift-invariant features using a Boosting framework. Features performing local convolutions followed by subsampling are used to achieve shift-invariance. Other systems using this type of features, e.g. Convolutional Neural Networks, use complex feed-forward networks with multiple layers. In contrast, the proposed system adds features one at a time using smoothing spline base classifiers. Feature training optimizes base classifier costs. Boosting sample-reweighting ensures features to be both descriptive and independent. Our system has a lower number of design parameters as comparable systems, so adapting the system to new problems is simple. Also, the stage-wise training makes it very scalable. Experimental results show the competitiveness of our approach.},
	doi = {10.1007/978-3-642-03798-6_13},
	author = {Thomas H{\"o}rnlein and Bernd J{\"a}hne and Herbert S{\"u}{\ss}e},
	editor = {Joachim Denzler and Gunther Notni}
}
@booklet {jaehne2008d,
	title = {Bildverarbeitung verlangt nach Fortschritt - Forschung und berufliche Weiterbildung werden zum A und O},
	year = {2008},
	url = {http://www.sensorreport.ch/sen_Inhalt_5_08.ebs},
	author = {Bernd J{\"a}hne}
}
@incollection {jaehne1999,
	title = {Bl{\"a}tter, Wind und Wellen. Unsichtbares wird sichtbar.},
	year = {1999},
	pages = {38--43},
	publisher = {dot-Verlag},
	author = {Bernd J{\"a}hne},
	editor = {G. Dotzler}
}
@article {jaehne1994a,
	title = {Bildverarbeitung f{\"u}r die Meeresforschung},
	journal = {Ruperto Carola},
	number = {3},
	year = {1994},
	pages = {10--15},
	doi = {10.5281/zenodo.14915},
	url = {http://www.uni-heidelberg.de/uni/presse/rc7/2.html},
	author = {Bernd J{\"a}hne}
}
@conference {riemer1991a,
	title = {Bildfolgenanalyse im Orts-Wellenzahl-Raum},
	booktitle = {Proc. 13. DAGM-Symposium zur Mustererkennung 1991, M{\"u}nchen},
	year = {1991},
	note = {DAGM main award},
	doi = {10.1007/978-3-662-08896-8_28},
	author = {Riemer, K. and Thomas Scholz and Bernd J{\"a}hne}
}
@conference {wierzimok1987,
	title = {Bildfolgenanalyse dreidimensionaler turbulenter Str{\"o}mungen},
	booktitle = {Proc. 9. DAGM-Symposium zur Mustererkennung 1987},
	volume = {149},
	year = {1987},
	pages = {288},
	publisher = {Springer},
	organization = {Springer},
	doi = {10.1007/978-3-662-22205-8_71},
	author = {Dietmar Wierzimok and Bernd J{\"a}hne and J. Dengler},
	editor = {E. Paulus}
}
@conference {jaehne1986,
	title = {Bildfolgenanalyse in der Umweltphysik: Wasseroberfl{\"a}chenwellen und Gasaustausch zwischen Atmosph{\"a}re und Gew{\"a}ssern},
	booktitle = {Proc. 8. DAGM-Symposium Mustererkennung 1986},
	year = {1986},
	note = {DAGM award},
	pages = {201--205},
	doi = {10.1007/978-3-642-71387-3_36},
	url = {http://www.ub.uni-heidelberg.de/archiv/18103},
	author = {Bernd J{\"a}hne}
}
