AIMC Topic: Pattern Recognition, Automated

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Learning a discriminant graph-based embedding with feature selection for image categorization.

Neural networks : the official journal of the International Neural Network Society Dec 27, 2018
Graph-based embedding methods are very useful for reducing the dimension of high-dimensional data and for extracting their relevant features. In this paper, we introduce a novel nonlinear method called Flexible Discriminant graph-based Embedding with...
Humans Pattern Recognition, Automated Algorithms Photic Stimulation Supervised Machine Learning
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Integrative Gene Selection on Gene Expression Data: Providing Biological Context to Traditional Approaches.

Journal of integrative bioinformatics Dec 22, 2018
The advance of high-throughput RNA-Sequencing techniques enables researchers to analyze the complete gene activity in particular cells. From the insights of such analyses, researchers can identify disease-specific expression profiles, thus understand...
Neoplasm Proteins Knowledge Bases Pattern Recognition, Automated Gene Expression Profiling Computational Biology Gene Expression Regulation, Neoplastic Algorithms Humans Neoplasms
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Fast animal pose estimation using deep neural networks.

Nature methods Dec 20, 2018
The need for automated and efficient systems for tracking full animal pose has increased with the complexity of behavioral data and analyses. Here we introduce LEAP (LEAP estimates animal pose), a deep-learning-based method for predicting the positio...
Pattern Recognition, Automated Behavior, Animal Locomotion Drosophila melanogaster Computer Graphics Mice Gait Automation Deep Learning User-Computer Interface Neural Networks, Computer Algorithms Animals Male
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PENYEK: Automated brown planthopper detection from imperfect sticky pad images using deep convolutional neural network.

PloS one Dec 20, 2018
Rice is a staple food in Asia and it contributes significantly to the Gross Domestic Product (GDP) of Malaysia and other developing countries. Brown Planthopper (BPH) causes high levels of economic loss in Malaysia. Identification of BPH presence and...
Insect Control Deep Learning Pattern Recognition, Automated Software Malaysia Agriculture Electronic Data Processing Algorithms Humans Oryza Environmental Monitoring Animals Neural Networks, Computer Insecta
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The Whole Is More Than Its Parts? From Explicit to Implicit Pose Normalization.

IEEE transactions on pattern analysis and machine intelligence Dec 18, 2018
Fine-grained classification describes the automated recognition of visually similar object categories like birds species. Previous works were usually based on explicit pose normalization, i.e., the detection and description of object parts. However, ...
Image Processing, Computer-Assisted Pattern Recognition, Automated Machine Learning Algorithms Neural Networks, Computer Animals
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Reconstructing Perceived Images From Human Brain Activities With Bayesian Deep Multiview Learning.

IEEE transactions on neural networks and learning systems Dec 12, 2018
Neural decoding, which aims to predict external visual stimuli information from evoked brain activities, plays an important role in understanding human visual system. Many existing methods are based on linear models, and most of them only focus on ei...
Deep Learning Image Processing, Computer-Assisted Bayes Theorem Neural Networks, Computer Brain Pattern Recognition, Automated Humans
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P_VggNet: A convolutional neural network (CNN) with pixel-based attention map.

PloS one Dec 12, 2018
Attention maps have been fused in the VggNet structure (EAC-Net) [1] and have shown significant improvement compared to that of the VggNet structure. However, in [1], E-Net was designed based on the facial action unit (AU) center and for facial AU de...
Humans Neural Networks, Computer Pattern Recognition, Automated Algorithms Image Enhancement Image Processing, Computer-Assisted Attention
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Visualization Methods for Image Transformation Convolutional Neural Networks.

IEEE transactions on neural networks and learning systems Dec 11, 2018
Convolutional neural networks (CNNs) are powerful machine learning models that have become the state of the art in several problems in the areas of computer vision and image processing. Nevertheless, the knowledge of why and how these models present ...
Image Processing, Computer-Assisted Pattern Recognition, Automated Humans Neural Networks, Computer
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Automated Abdominal Segmentation of CT Scans for Body Composition Analysis Using Deep Learning.

Radiology Dec 11, 2018
Purpose To develop and evaluate a fully automated algorithm for segmenting the abdomen from CT to quantify body composition. Materials and Methods For this retrospective study, a convolutional neural network based on the U-Net architecture was traine...
Humans Radiographic Image Interpretation, Computer-Assisted Pattern Recognition, Automated Radiography, Abdominal Adult Tomography, X-Ray Computed Liver Neoplasms Middle Aged Aged Carcinoma, Hepatocellular Deep Learning Algorithms Aged, 80 and over Body Composition Retrospective Studies
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Morphometric analysis of peripheral myelinated nerve fibers through deep learning.

Journal of the peripheral nervous system : JPNS Dec 11, 2018
Irrespective of initial causes of neurological diseases, these disorders usually exhibit two key pathological changes-axonal loss or demyelination or a mixture of the two. Therefore, vigorous quantification of myelin and axons is essential in studyin...
Animals Deep Learning Mice Axons Pattern Recognition, Automated Nerve Fibers, Myelinated Mice, Inbred C57BL Mice, Knockout Microscopy
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