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Computer Aided Diagnosis for Anti-Nuclear Antibodies HEp-2 images: Progress and challenges., , , , , and . Pattern Recognit. Lett., (2016)HEp-2 staining pattern recognition at cell and specimen levels: Datasets, algorithms and results., , , , , and . Pattern Recognit. Lett., (2016)Benchmarking human epithelial type 2 interphase cells classification methods on a very large dataset., , , , and . Artif. Intell. Medicine, 65 (3): 239-250 (2015)Deep Adaptive Few Example Learning for Microscopy Image Cell Counting., , , , , and . DICTA, page 1-7. IEEE, (2021)An Automatic Image Based Single Dilution Method for End Point Titre Quantitation of Antinuclear Antibodies Tests Using HEp-2 Cells., , , and . DICTA, page 1-6. IEEE Computer Society, (2011)SlideNet: Fast and Accurate Slide Quality Assessment Based on Deep Neural Networks., , , , , , , and . ICPR, page 2314-2319. IEEE Computer Society, (2018)Visual learning and classification of human epithelial type 2 cell images through spontaneous activity patterns., , , , and . Pattern Recognit., 47 (7): 2325-2337 (2014)Automation of species-specific cyanobacteria phycocyanin fluorescence compensation using machine learning classification., , , , and . Ecol. Informatics, (2022)Visualising Breath., , and . EVA, BCS, (2012)Discovering discriminative cell attributes for HEp-2 specimen image classification., , and . WACV, page 423-430. IEEE Computer Society, (2014)