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2014

J. H. Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Kim, S., Kausler, B. X., Kröger, T., Lellmann, J., Komodakis, N., Savchynskyy, B., and Rother, C., “A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems”, CoRR, vol. abs/1404.0533, 2014.

Technical Report (3.32 MB)

J. H. Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Kim, S., Kausler, B. X., Kröger, T., Lellmann, J., Komodakis, N., Savchynskyy, B., and Rother, C., “A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems”, CoRR, vol. abs/1404.0533, 2014.

Technical Report (3.32 MB)

J. H. Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Kim, S., Kausler, B. X., Kröger, T., Lellmann, J., Komodakis, N., Savchynskyy, B., and Rother, C., “A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems”, CoRR, vol. abs/1404.0533, 2014.

Technical Report (3.32 MB)

J. H. Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Kim, S., Kausler, B. X., Kröger, T., Lellmann, J., Komodakis, N., Savchynskyy, B., and Rother, C., “A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems”, CoRR, vol. abs/1404.0533, 2014.

Technical Report (3.32 MB)

J. H. Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Kim, S., Kausler, B. X., Kröger, T., Lellmann, J., Komodakis, N., Savchynskyy, B., and Rother, C., “A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems”, CoRR, vol. abs/1404.0533, 2014.

Technical Report (3.32 MB)

M. Kandemir and Hamprecht, F. A., “Computer-aided diagnosis from weak supervision: A benchmarking study”, Computerized Medical Imaging and Graphics, vol. 42, pp. 44-50, 2014.

Technical Report (4.28 MB)

L. Maier-Hein, Mersmann, S., Kondermann, D., Stock, C., Kenngott, H., Sanchez, A., Wagner, M., Preukschas, A., Wekerle, A. - L., Helfert, S., Bodenstedt, S., and Speidel, S., “Crowdsourcing for reference correspondence generation in endoscopic images”, in MICCAI, 2014.

L. Maier-Hein, Mersmann, S., Kondermann, D., Stock, C., Kenngott, H., Sanchez, A., Wagner, M., Preukschas, A., Wekerle, A. - L., Helfert, S., Bodenstedt, S., and Speidel, S., “Crowdsourcing for reference correspondence generation in endoscopic images”, in MICCAI, 2014.

T. Beier, Kröger, T., Kappes, J. H., Köthe, U., and Hamprecht, F. A., “Cut, Glue and Cut: A Fast, Approximate Solver for Multicut Partitioning”, in 2014 {IEEE} Conference on Computer Vision and Pattern Recognition, {CVPR} 2014, Columbus, OH, USA, June 23-28, 2014, 2014.

Technical Report (10.06 MB)

T. Beier, Kröger, T., Kappes, J. H., Köthe, U., and Hamprecht, F. A., “Cut, Glue and Cut: A Fast, Approximate Solver for Multicut Partitioning”, in 2014 {IEEE} Conference on Computer Vision and Pattern Recognition, {CVPR} 2014, Columbus, OH, USA, June 23-28, 2014, 2014.

Technical Report (10.06 MB)

T. Beier, Kröger, T., Kappes, J. H., Köthe, U., and Hamprecht, F. A., “Cut, Glue and Cut: A Fast, Approximate Solver for Multicut Partitioning”, in 2014 {IEEE} Conference on Computer Vision and Pattern Recognition, {CVPR} 2014, Columbus, OH, USA, June 23-28, 2014, 2014.

Technical Report (10.06 MB)

M. Kandemir, Feuchtinger, A., Walch, A., and Hamprecht, F. A., “Digital Pathology: Multiple instance learning can detect Barrett'scancer”, ISBI. Proceedings. pp. 1348-1351, 2014.

Technical Report (2.86 MB)

M. Kandemir, Zhang, C., and Hamprecht, F. A., “Empowering multiple instance histopathology cancer diagnosis by cell graphs”, in MICCAI. Proceedings, 2014, vol. 8674, pp. 228-235.

Technical Report (1.76 MB)

M. Kandemir, Rubio, J. C., Schmidt, U., Wojek, C., Welbl, J., Ommer, B., and Hamprecht, F. A., “Event Detection by Feature Unpredictability in Phase-Contrast Videos of Cell Cultures”, in Medical Image Computing and Computer-Assisted Intervention, 2014, p. 154--161.

Technical Report (2 MB)

M. Kandemir, Rubio, J. C., Schmidt, U., Welbl, J., Ommer, B., and Hamprecht, F. A., “Event Detection by Feature Unpredictability in Phase-Contrast Videos of Cell Cultures”, in MICCAI. Proceedings, 2014, pp. 154-161.

Paper (2 MB)

M. Knorr, Esparza, J., Niehsen, W., and Stiller, C., “Extrinsic calibration of a fisheye multi-camera setup using overlapping fields of view”, in Intelligent Vehicles Symposium Proceedings, 2014, p. 1276--1281.

K. Ellen Krall and Jähne, B., “First laboratory study of air-sea gas exchange at hurricane wind speeds”, Ocean Sci., vol. 10, p. 257--265, 2014.

C. Kräuter, Trofimova, D., Kiefhaber, D., Krah, N., and Jähne, B., “High resolution 2-D fluorescence imaging of the mass boundary layer thickness at free water surfaces”, J. Europ. Opt. Soc. Rap. Public., vol. 9, p. 14016, 2014.

C. Kräuter, Trofimova, D., Kiefhaber, D., Krah, N., and Jähne, B., “High resolution 2-D fluorescence imaging of the mass boundary layer thickness at free water surfaces”, J. Europ. Opt. Soc. Rap. Public., vol. 9, p. 14016, 2014.

C. Kräuter, Trofimova, D., Kiefhaber, D., Krah, N., and Jähne, B., “High resolution 2-D fluorescence imaging of the mass boundary layer thickness at free water surfaces”, J. Europ. Opt. Soc. Rap. Public., vol. 9, p. 14016, 2014.

M. Hornáček, Besse, F., Kautz, J., Fitzgibbon, A., and Rother, C., “Highly overparameterized optical flow using PatchMatch belief propagation”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2014, vol. 8691 LNCS, pp. 220–234.

C. Kräuter, Trofimova, D., Nagel, L., and Jähne, B., “High-resolution 2-D fluorescence imaging of gas transfer at a free water surface”, in Ocean Science Meeting, 23--28. 02. 2014, Honolulu Hawaii, 2014.

D. Kiefhaber, Reith, S., Rocholz, R., and Jähne, B., “High-speed imaging of short wind waves by shape from refraction”, J. Europ. Opt. Soc. Rap. Public., vol. 9, p. 14015, 2014.

J. Kleesiek, Biller, A., Urban, G., Köthe, U., Bendszus, M., and Hamprecht, F. A., “ilastik for Multi-modal Brain Tumor Segmentation”, in MICCAI BraTS (Brain Tumor Segmentation) Challenge. Proceedings, 3rdplace, 2014, pp. 12-17.

Technical Report (405.91 KB)

J. Kleesiek, Biller, A., Urban, G., Köthe, U., Bendszus, M., and Hamprecht, F. A., “ilastik for Multi-modal Brain Tumor Segmentation”, in MICCAI BraTS (Brain Tumor Segmentation) Challenge. Proceedings, 3rdplace, 2014, pp. 12-17.

Technical Report (405.91 KB)

M. Kandemir and Hamprecht, F. A., “Instance Label Prediction by Dirichlet Process Multiple Instance Learning”, in UAI. Proceedings, 2014.

Technical Report (4.26 MB)

T. Kröger, “Learning-based Segmentation for Connectomics”. University of Heidelberg, 2014.

J. H. Kappes, Beier, T., and Schnörr, C., “MAP-Inference on Large Scale Higher-Order Discrete Graphical Models by Fusion Moves”, in Computer Vision - {ECCV} 2014 Workshops - Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part {II}, 2014.

Technical Report (557.49 KB)

J. Hendrik Kappes, Beier, T., and Schnörr, C., “MAP-Inference on Large Scale Higher-Order Discrete Graphical Models by Fusion Moves”, in International Workshop on Graphical Models in Computer Vision, 2014.

D. Kiefhaber, Zappa, C. J., and Jähne, B., “Measurement of wind waves statistics from specular reflections”, in Ocean Science Meeting, 23--28. 02. 2014, Honolulu Hawaii, 2014.

E. Mesarchaki, Kräuter, C., Krall, K. Ellen, Bopp, M., Helleis, F., Williams, J., and Jähne, B., “Measuring air-sea gas exchange velocities in a large scale annular wind-wave tank”, Ocean Sci. Discuss., vol. 11, p. 1643--1689, 2014.

E. Mesarchaki, Kräuter, C., Krall, K. Ellen, Bopp, M., Helleis, F., Williams, J., and Jähne, B., “Measuring air-sea gas exchange velocities in a large scale annular wind-wave tank”, Ocean Sci. Discuss., vol. 11, p. 1643--1689, 2014.

G. Urban, Bendszus, M., Hamprecht, F. A., and Kleesiek, J., “Multi-modal Brain Tumor Segmentation using Deep Convolutional NeuralNetworks”, in MICCAI BraTS (Brain Tumor Segmentation) Challenge. Proceedings, winningcontribution, 2014, pp. 31-35.

C. N. Straehle, Kandemir, M., Köthe, U., and Hamprecht, F. A., “Multiple instance learning with response-optimized random forests”, in ICPR. Proceedings, 2014, pp. 3768 - 3773.

Technical Report (296.66 KB)

C. N. Straehle, Kandemir, M., Köthe, U., and Hamprecht, F. A., “Multiple instance learning with response-optimized random forests”, in ICPR. Proceedings, 2014, pp. 3768 - 3773.

Technical Report (296.66 KB)

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