Henry Schütze, PhD

Institut für Neuro- und Bioinformatik
Ratzeburger Allee 160
23562 Lübeck
Email: | inb(at)inb.uni-luebeck.de |
Phone: | +49 451 3101 5501 |
Fax: | +49 451 3101 5504 |
MATLAB toolbox orthogonal_dictionary_learning
The toolbox orthogonal_dictionary_learning provides a MATLAB implementation of several orthogonal dictionary learning methods for sparse coding.
Publikationen
2016
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Schütze, Henry and Barth, Erhardt and Martinetz, Thomas: Learning Efficient Data Representations with Orthogonal Sparse Coding. IEEE Transactions on Computational Imaging, no. 2, pp. 177-189, 09, 2016
@article{ScBaMa16, author = {Sch{\"u}tze, Henry and Barth, Erhardt and Martinetz, Thomas}, title = {{L}earning {E}fficient {D}ata {R}epresentations with {O}rthogonal {S}parse {C}oding}, journal = {IEEE Transactions on Computational Imaging}, volume = {2}, number = {3}, month = {09}, pages = {177--189}, ISSN = {2333-9403}, year = {2016}, doi = {10.1109/TCI.2016.2557065}, url = {https://www.inb.uni-luebeck.de/fileadmin/files/publications/inb-publications/pdfs/ScBaMa16.pdf} }
2015
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Schütze, Henry and Barth, Erhardt and Martinetz, Thomas: Learning Orthogonal Sparse Representations by Using Geodesic Flow Optimization. in IJCNN 2015 Conference Proceedings, pp. 15540:1-8, 2015
@inproceedings{ScBaMa15, author={Sch{\"u}tze, Henry and Barth, Erhardt and Martinetz, Thomas}, title={{L}earning {O}rthogonal {S}parse {R}epresentations by {U}sing {G}eodesic {F}low {O}ptimization}, booktitle = {IJCNN 2015 Conference Proceedings}, series = {The International Joint Conference on Neural Networks}, year = {2015}, pages = {15540:1--8}, url = {https://www.inb.uni-luebeck.de/fileadmin/files/publications/inb-publications/pdfs/ScBaMa15.pdf} }
2014
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Schütze, Henry and Barth, Erhardt and Martinetz, Thomas: An adaptive hierarchical sensing scheme for sparse signals. in Human Vision and Electronic Imaging XIX, no. 9014, pp. 15:1-8, 2014
@inproceedings{ScBaMa14, author={Sch{\"u}tze, Henry and Barth, Erhardt and Martinetz, Thomas}, title={An adaptive hierarchical sensing scheme for sparse signals}, booktitle = {Human Vision and Electronic Imaging XIX}, series = {Proc. of SPIE Electronic Imaging}, editor = {Bernice E. Rogowitz and Thrasyvoulos N. Pappas and Huib de Ridder}, volume = {9014}, pages = {15:1--8}, year = {2014}, url = {https://www.inb.uni-luebeck.de/fileadmin/files/publications/inb-publications/pdfs/ScBaMa14.pdf} }
2013
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Schütze, Henry and Barth, Erhardt and Martinetz, Thomas: Learning Orthogonal Bases for k-Sparse Representations. in Workshop New Challenges in Neural Computation 2013, no. 02, pp. 119-120, 2013
@inproceedings{ScBaMa13, author={Sch{\"u}tze, Henry and Barth, Erhardt and Martinetz, Thomas}, title = {{L}earning {O}rthogonal {B}ases for k-{S}parse {R}epresentations}, booktitle = {Workshop New Challenges in Neural Computation 2013}, editor = {Barbara Hammer and Thomas Martinetz and Thomas Villmann}, series ={Machine Learning Reports}, volume = {02}, year = {2013}, pages = {119--120}, note = {Short Paper}, url = {https://www.inb.uni-luebeck.de/fileadmin/files/publications/inb-publications/pdfs/ScBaMa13.pdf} }
2012
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Henry Schütze and Thomas Martinetz and Silke Anders and Amir Madany Mamlouk: A Multivariate Approach to Estimate Complexity of FMRI Time Series. in Artificial Neural Networks and Machine Learning - ICANN 2012, 22nd International Conference, Lausanne, Switzerland, September 11-14, 2012, Proceedings, Part II, no. 7553, pp. 540-547, Springer, 2012
@inproceedings{ScMaAnMa12, author = {Henry Sch{\"u}tze and Thomas Martinetz and Silke Anders and Amir Madany Mamlouk}, title = {A {M}ultivariate {A}pproach to {E}stimate {C}omplexity of {F}{MRI} {T}ime {S}eries}, editor = {Alessandro E.P. Villa and W{\l}odzis{\l}aw Duch and P{\'{e}}ter {\'{E}}rdi and Francesco Masulli and G{\"u}nter Palm}, booktitle = {Artificial Neural Networks and Machine Learning - ICANN 2012, 22nd International Conference, Lausanne, Switzerland, September 11-14, 2012, Proceedings, Part II}, year = {2012}, pages = {540--547}, publisher = {Springer}, series = {Lecture Notes in Computer Science}, volume = {7553}, url = {https://www.inb.uni-luebeck.de/fileadmin/files/publications/inb-publications/pdfs/ScMaAnMa12.pdf} }