AIMC Topic: Deep Learning

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Grid-like units help deep learning agent to navigate.

Learning & behavior Mar 1, 2019
An artificial-intelligence model based on deep learning developed units in a hidden layer that resembled mammalian grid cells in the hippocampus when the agent was taught to integrate paths. The full model performed sophisticated navigational tasks-i...
Deep Learning Hippocampus Grid Cells Humans Animals
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A sparse deep learning model for privacy attack on remote sensing images.

Mathematical biosciences and engineering : MBE Feb 20, 2019
Deep learning tools have been a new way for privacy attacks on remote sensing images. However, since labeled data of privacy objects in remote sensing images are less, the samples for training are commonly small. Besides, traditional deep neural netw...
Geographic Information Systems Algorithms Data Interpretation, Statistical Neural Networks, Computer Deep Learning Remote Sensing Technology Image Processing, Computer-Assisted Computer Simulation Software Privacy Reproducibility of Results
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Using neuroscience to develop artificial intelligence.

Science (New York, N.Y.) Feb 15, 2019
Brain Learning Deep Learning Humans Neural Networks, Computer Artificial Intelligence Neurosciences
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Artificial intelligence in medical imaging of the liver.

World journal of gastroenterology Feb 14, 2019
Artificial intelligence (AI), particularly deep learning algorithms, is gaining extensive attention for its excellent performance in image-recognition tasks. They can automatically make a quantitative assessment of complex medical image characteristi...
Liver Diagnostic Imaging Liver Diseases Algorithms Deep Learning Humans Neural Networks, Computer Artificial Intelligence Machine Learning
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Deep learning in omics: a survey and guideline.

Briefings in functional genomics Feb 14, 2019
Omics, such as genomics, transcriptome and proteomics, has been affected by the era of big data. A huge amount of high dimensional and complex structured data has made it no longer applicable for conventional machine learning algorithms. Fortunately,...
Genomics Computational Biology Proteomics Deep Learning Surveys and Questionnaires Humans Guidelines as Topic Algorithms Transcriptome
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Artificial intelligence alone won't solve the complexity of Earth sciences.

Nature Feb 1, 2019
Earth Sciences Social Problems Artificial Intelligence Deep Learning
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Identifying short disorder-to-order binding regions in disordered proteins with a deep convolutional neural network method.

Journal of bioinformatics and computational biology Feb 1, 2019
Molecular recognition features (MoRFs) are key functional regions of intrinsically disordered proteins (IDPs), which play important roles in the molecular interaction network of cells and are implicated in many serious human diseases. Identifying MoR...
Binding Sites Humans Amino Acid Sequence Intrinsically Disordered Proteins Computational Biology Membrane Proteins Neural Networks, Computer Databases, Protein Deep Learning Protein Binding
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Using two-dimensional convolutional neural networks for identifying GTP binding sites in Rab proteins.

Journal of bioinformatics and computational biology Feb 1, 2019
Deep learning has been increasingly and widely used to solve numerous problems in various fields with state-of-the-art performance. It can also be applied in bioinformatics to reduce the requirement for feature extraction and reach high performance. ...
Deep Learning Computational Biology Databases, Protein Amino Acids Amino Acid Sequence Binding Sites Humans Neural Networks, Computer rab GTP-Binding Proteins Guanosine Triphosphate
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Deep Learning for Prediction of AMD Progression: A Pilot Study.

Investigative ophthalmology & visual science Feb 1, 2019
PURPOSE: To develop and assess a method for predicting the likelihood of converting from early/intermediate to advanced wet age-related macular degeneration (AMD) using optical coherence tomography (OCT) imaging and methods of deep learning.
Tomography, Optical Coherence Wet Macular Degeneration Pilot Projects ROC Curve Follow-Up Studies Diagnosis, Computer-Assisted Deep Learning Humans Neural Networks, Computer Machine Learning Female Aged Aged, 80 and over Male Middle Aged Disease Progression
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Segmentation of Nuclei in Histopathology Images by Deep Regression of the Distance Map.

IEEE transactions on medical imaging Feb 1, 2019
The advent of digital pathology provides us with the challenging opportunity to automatically analyze whole slides of diseased tissue in order to derive quantitative profiles that can be used for diagnosis and prognosis tasks. In particular, for the ...
Image Interpretation, Computer-Assisted Cell Nucleus Histological Techniques Databases, Factual Neoplasms Deep Learning Humans
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