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Semantic Analysis of Biological Imaging Data: Challenges and Opportunities., , , , , and . Int. J. Semantic Comput., 1 (1): 67-85 (2007)Self-Adjusting Models for Semi-supervised Learning in Partially Observed Settings., , , and . ICDM, page 21-30. IEEE Computer Society, (2012)Learning with a non-exhaustive training dataset: a case study: detection of bacteria cultures using optical-scattering technology., , , , and . KDD, page 279-288. ACM, (2009)A low complexity speck-based codec for multispectral fluorescence microscopic images., , and . ICASSP, page 694-697. IEEE, (2010)Noise reduction and 3D visualization of confocal microscopy images., , , , and . Computational Imaging, volume 5299 of SPIE Proceedings, page 63-72. SPIE, (2004)Non-exhaustive Learning for Bacteria Detection., , , , and . NBiS, page 206-211. IEEE Computer Society, (2009)Simplicity of Kmeans Versus Deepness of Deep Learning: A Case of Unsupervised Feature Learning with Limited Data., , , , and . ICMLA, page 883-888. IEEE, (2015)Interactive volume visualization of cellular structures., , , and . Computational Imaging, volume 6065 of SPIE Proceedings, page 60651D. SPIE, (2006)Phenotyping Immune Cells in Tumor and Healthy Tissue Using Flow Cytometry Data., , , , , , and . BCB, page 73-78. ACM, (2018)A novel statistical methodology for quantifying the spatial arrangements of axons in peripheral nerves., , , , , , , , , and . CoRR, (2022)