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Unsupervised Cross-Domain Feature Extraction for Single Blood Cell Image Classification.

R. Salehi, A. Sadafi, A. Gruber, P. Lienemann, N. Navab, S. Albarqouni, and C. Marr. MICCAI (3), volume 13433 of Lecture Notes in Computer Science, page 739-748. Springer, (2022)

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Carsten Marr

Ludwig Marr

Diethard Marr

Jürgen Marr

Stefanie Marr

Other publications of authors with the same name

Topology regulates pattern formation capacity of binary cellular automata on graphsC. Marr, and M. Hütt. Physica A: Statistical Mechanics and its Applications, (Aug 15, 2005)Active Learning Enhances Classification of Histopathology Whole Slide Images with Attention-Based Multiple Instance Learning.A. Sadafi, N. Navab, and C. Marr. ISBI, page 1-5. IEEE, (2023)Fourier Transform of Percoll Gradients Boosts CNN Classification of Hereditary Hemolytic Anemias.A. Sadafi, L. Sans, A. Makhro, L. Livshits, N. Navab, A. Bogdanova, S. Albarqouni, and C. Marr. ISBI, page 966-970. IEEE, (2021)In-Silico Staining from Bright-Field and Fluorescent Images Using Deep Learning.D. Waibel, U. Tiemann, V. Lupperger, H. Semb, and C. Marr. ICANN (3), volume 11729 of Lecture Notes in Computer Science, page 184-186. Springer, (2019)Self-Supervised Multiple Instance Learning for Acute Myeloid Leukemia Classification.S. Kazeminia, M. Joosten, D. Bosnacki, and C. Marr. CoRR, (2024)Capturing Shape Information with Multi-scale Topological Loss Terms for 3D Reconstruction.D. Waibel, S. Atwell, M. Meier, C. Marr, and B. Rieck. MICCAI (4), volume 13434 of Lecture Notes in Computer Science, page 150-159. Springer, (2022)M-HOF-Opt: Multi-Objective Hierarchical Output Feedback Optimization via Multiplier Induced Loss Landscape Scheduling.X. Sun, N. Chen, A. Gossmann, Y. Xing, C. Feistner, E. Dorigatt, F. Drost, D. Scarcella, L. Beer, and C. Marr. CoRR, (2024)DinoBloom: A Foundation Model for Generalizable Cell Embeddings in Hematology.V. Koch, S. Wagner, S. Kazeminia, E. Sancar, M. Hehr, J. Schnabel, T. Peng, and C. Marr. CoRR, (2024)Low-Resource Finetuning of Foundation Models Beats State-of-the-Art in Histopathology.B. Roth, V. Koch, S. Wagner, J. Schnabel, C. Marr, and T. Peng. ISBI, page 1-5. IEEE, (2024)LNA++: Linear Noise Approximation with First and Second Order Sensitivities.J. Feigelman, D. Weindl, F. Theis, C. Marr, and J. Hasenauer. CMSB, volume 11095 of Lecture Notes in Computer Science, page 300-306. Springer, (2018)

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Disambiguation of "Marr, Carsten"

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Unsupervised Cross-Domain Feature Extraction for Single Blood Cell Image Classification.

Please choose a person to relate this publication to

Carsten Marr

Ludwig Marr

Diethard Marr

Jürgen Marr

Stefanie Marr

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Marr, Carsten"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Unsupervised Cross-Domain Feature Extraction for Single Blood Cell Image Classification.

Please choose a person to relate this publication to

Carsten Marr

Ludwig Marr

Diethard Marr

Jürgen Marr

Stefanie Marr

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Unsupervised Cross-Domain Feature Extraction for Single Blood Cell Image Classification.