AIMC Topic: Pattern Recognition, Automated

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Minimum Entropy Rate Simplification of Stochastic Processes.

IEEE transactions on pattern analysis and machine intelligence Feb 23, 2016
We propose minimum entropy rate simplification (MERS), an information-theoretic, parameterization-independent framework for simplifying generative models of stochastic processes. Applications include improving model quality for sampling tasks by conc...
Animals Pattern Recognition, Automated Models, Statistical Entropy Models, Biological Speech Production Measurement Sound Spectrography Humans Machine Learning Algorithms Computer Simulation
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Control-group feature normalization for multivariate pattern analysis of structural MRI data using the support vector machine.

NeuroImage Feb 23, 2016
Normalization of feature vector values is a common practice in machine learning. Generally, each feature value is standardized to the unit hypercube or by normalizing to zero mean and unit variance. Classification decisions based on support vector ma...
Multivariate Analysis Computer Simulation Brain Mapping Female Signal Processing, Computer-Assisted Humans Sensitivity and Specificity Reproducibility of Results Alzheimer Disease Brain Aged Pattern Recognition, Automated Male Support Vector Machine Magnetic Resonance Imaging
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Extending (Q)SARs to incorporate proprietary knowledge for regulatory purposes: A case study using aromatic amine mutagenicity.

Regulatory toxicology and pharmacology : RTP Feb 13, 2016
Statistical-based and expert rule-based models built using public domain mutagenicity knowledge and data are routinely used for computational (Q)SAR assessments of pharmaceutical impurities in line with the approach recommended in the ICH M7 guidelin...
Quantitative Structure-Activity Relationship Mutagenesis Mutagenicity Tests Amines Knowledge Bases Data Mining Pattern Recognition, Automated Mutagens Humans Databases, Factual Animals Computer Simulation Risk Assessment Models, Molecular Molecular Structure
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Localization and Classification of Paddy Field Pests using a Saliency Map and Deep Convolutional Neural Network.

Scientific reports Feb 11, 2016
We present a pipeline for the visual localization and classification of agricultural pest insects by computing a saliency map and applying deep convolutional neural network (DCNN) learning. First, we used a global contrast region-based approach to co...
China Insecta Crops, Agricultural Neural Networks, Computer Pattern Recognition, Automated Algorithms Databases, Factual Animals
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Enhancing the Prediction of Transmembrane β-Barrel Segments with Chain Learning and Feature Sparse Representation.

IEEE/ACM transactions on computational biology and bioinformatics Feb 11, 2016
Transmembrane β-barrels (TMBs) are one important class of membrane proteins that play crucial functions in the cell. Membrane proteins are difficult wet-lab targets of structural biology, which call for accurate computational prediction approaches. H...
Machine Learning Algorithms Computer Simulation Sequence Analysis, Protein Amino Acid Sequence Pattern Recognition, Automated Protein Structure, Secondary Membrane Proteins Molecular Sequence Data Databases, Protein Models, Chemical
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HEp-2 Cell Image Classification With Deep Convolutional Neural Networks.

IEEE journal of biomedical and health informatics Feb 8, 2016
Efficient Human Epithelial-2 cell image classification can facilitate the diagnosis of many autoimmune diseases. This paper proposes an automatic framework for this classification task, by utilizing the deep convolutional neural networks (CNNs) which...
Humans Neural Networks, Computer Algorithms Image Processing, Computer-Assisted Fluorescent Antibody Technique, Indirect Cell Line Epithelial Cells Coloring Agents Pattern Recognition, Automated
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A combined deep-learning and deformable-model approach to fully automatic segmentation of the left ventricle in cardiac MRI.

Medical image analysis Feb 6, 2016
Segmentation of the left ventricle (LV) from cardiac magnetic resonance imaging (MRI) datasets is an essential step for calculation of clinical indices such as ventricular volume and ejection fraction. In this work, we employ deep learning algorithms...
Reproducibility of Results Sensitivity and Specificity Heart Ventricles Ventricular Dysfunction, Left Image Interpretation, Computer-Assisted Pattern Recognition, Automated Image Enhancement Models, Cardiovascular Humans Machine Learning Algorithms Computer Simulation Subtraction Technique Magnetic Resonance Imaging, Cine
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Adapting content-based image retrieval techniques for the semantic annotation of medical images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Feb 4, 2016
The automatic annotation of medical images is a prerequisite for building comprehensive semantic archives that can be used to enhance evidence-based diagnosis, physician education, and biomedical research. Annotation also has important applications i...
Terminology as Topic Radiology Information Systems Radiographic Image Enhancement Database Management Systems Imaging, Three-Dimensional Liver Natural Language Processing Radiographic Image Interpretation, Computer-Assisted Data Mining Documentation Semantics Pattern Recognition, Automated Algorithms Tomography, X-Ray Computed Humans Reproducibility of Results Sensitivity and Specificity Machine Learning
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Drug-Drug Interaction Extraction via Convolutional Neural Networks.

Computational and mathematical methods in medicine Jan 31, 2016
Drug-drug interaction (DDI) extraction as a typical relation extraction task in natural language processing (NLP) has always attracted great attention. Most state-of-the-art DDI extraction systems are based on support vector machines (SVM) with a lar...
Natural Language Processing Pattern Recognition, Automated Algorithms Humans Drug Interactions Neural Networks, Computer Data Mining Support Vector Machine Machine Learning Semantics Models, Statistical Regression Analysis
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Body-Based Gender Recognition Using Images from Visible and Thermal Cameras.

Sensors (Basel, Switzerland) Jan 27, 2016
Gender information has many useful applications in computer vision systems, such as surveillance systems, counting the number of males and females in a shopping mall, accessing control systems in restricted areas, or any human-computer interaction sy...
Face Pattern Recognition, Automated Biometry Gender Identity Female Male Humans Image Interpretation, Computer-Assisted Artificial Intelligence Algorithms
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