6 citations · 10 across the 3 of their papers we have counts for
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cs.CV2019★ 6 cited
Supervised and Unsupervised End-to-End Deep Learning for Gene Ontology Classification of Neural In Situ Hybridization Images
Ido Cohen, Eli David, Nathan S. Netanyahu
In recent years, large datasets of high-resolution mammalian neural images have become available, which has prompted active research on the analysis of gene expression data. Tradit…
cs.CV2017★ 4 cited
DeepBrain: Functional Representation of Neural In-Situ Hybridization Images for Gene Ontology Classification Using Deep Convolutional Autoencoders
Ido Cohen, Eli David, Nathan S. Netanyahu +2
This paper presents a novel deep learning-based method for learning a functional representation of mammalian neural images. The method uses a deep convolutional denoising autoencod…