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Accurate segmentation of nuclei in pathological images via sparse reconstruction and deep convolutional networks.

, , , , , , and . Neurocomputing, (2017)

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Accurate segmentation of nuclei in pathological images via sparse reconstruction and deep convolutional networks., , , , , , and . Neurocomputing, (2017)CNNPSP: Pseudouridine Sites Prediction Based on Deep Learning., , , and . IDEAL (1), volume 11871 of Lecture Notes in Computer Science, page 291-301. Springer, (2019)Inter-vehicle dynamic data management and communication design., , , and . INDIN, page 594-598. IEEE, (2009)Multi-task deep learning for fine-grained classification and grading in breast cancer histopathological images., , , , , , , , and . Multim. Tools Appl., 79 (21-22): 14509-14528 (2020)Multi-task Deep Learning for Fine-Grained Classification/Grading in Breast Cancer Histopathological Images., , , , , , , , and . Cognitive Internet of Things, volume 810 of Studies in Computational Intelligence, Springer, (2019)Identifying RNA-binding proteins using multi-label deep learning., , , and . Sci. China Inf. Sci., 62 (1): 19103:1-19103:3 (2019)Predicting protein-ATP binding sites from primary sequence through fusing bi-profile sampling of multi-view features., , , , , and . BMC Bioinform., (2012)Predicting protein-RNA interaction amino acids using random forest based on submodularity subset selection., , , and . Comput. Biol. Chem., (2014)Predicting pupylation sites in prokaryotic proteins using pseudo-amino acid composition and extreme learning machine., and . Neurocomputing, (2014)