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Lecture Notes in Computer Science
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 autoencoder (CDAE) for generating an invariant, compact representation of in situ hybridization (ISH) images. While most existing methods for bio-imaging analysis were not developed to handle images with highly complex anatomical structures, the results presented in this paper show that functional representation extracted bydoi:10.1007/978-3-319-68612-7_33 fatcat:2og6qrydj5h5vbs3jg6cjgqq5y