AIMC Topic: Pattern Recognition, Automated

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Discretely-constrained deep network for weakly supervised segmentation.

Neural networks : the official journal of the International Neural Network Society Jul 18, 2020
An efficient strategy for weakly-supervised segmentation is to impose constraints or regularization priors on target regions. Recent efforts have focused on incorporating such constraints in the training of convolutional neural networks (CNN), howeve...
Algorithms Image Processing, Computer-Assisted Supervised Machine Learning Humans Neural Networks, Computer Pattern Recognition, Automated
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High-Resolution Radar Target Recognition via Inception-Based VGG (IVGG) Networks.

Computational intelligence and neuroscience Jul 18, 2020
Aiming at high-resolution radar target recognition, new convolutional neural networks, namely, Inception-based VGG (IVGG) networks, are proposed to classify and recognize different targets in high range resolution profile (HRRP) and synthetic apertur...
Neural Networks, Computer Pattern Recognition, Automated Radar
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Automatic CT image segmentation of maxillary sinus based on VGG network and improved V-Net.

International journal of computer assisted radiology and surgery Jul 16, 2020
PURPOSE: The analysis of the maxillary sinus (MS) can provide an assessment for many clinical diagnoses, so accurate CT image segmentation of the MS is essential. However, common segmentation methods are mainly done by experienced doctors manually, a...
Humans Imaging, Three-Dimensional Image Processing, Computer-Assisted Models, Statistical Maxillary Sinus Pattern Recognition, Automated False Positive Reactions Tomography, X-Ray Computed Reproducibility of Results Diagnosis, Computer-Assisted Neural Networks, Computer Software Algorithms
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Manual segmentation versus semi-automated segmentation for quantifying vestibular schwannoma volume on MRI.

International journal of computer assisted radiology and surgery Jul 16, 2020
PURPOSE: Management of vestibular schwannoma (VS) is based on tumour size as observed on T1 MRI scans with contrast agent injection. The current clinical practice is to measure the diameter of the tumour in its largest dimension. It has been shown th...
Neuroma, Acoustic Contrast Media Magnetic Resonance Imaging Automation Pattern Recognition, Automated Neuroimaging Neurilemmoma Reproducibility of Results Diagnosis, Computer-Assisted Image Processing, Computer-Assisted Machine Learning Software Algorithms Humans
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Exploiting defective RRAM array as synapses of HTM spatial pooler with boost-factor adjustment scheme for defect-tolerant neuromorphic systems.

Scientific reports Jul 16, 2020
A crossbar array architecture employing resistive switching memory (RRAM) as a synaptic element accelerates vector-matrix multiplication in a parallel fashion, enabling energy-efficient pattern recognition. To implement the function of the synapse in...
Synapses Transistors, Electronic Pattern Recognition, Automated Memory Neocortex Computer Simulation Data Management Data Accuracy Neural Networks, Computer Software Algorithms Humans
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Automated identification of chest radiographs with referable abnormality with deep learning: need for recalibration.

European radiology Jul 14, 2020
OBJECTIVES: To evaluate the calibration of a deep learning (DL) model in a diagnostic cohort and to improve model's calibration through recalibration procedures.
Retrospective Studies Female Reproducibility of Results Humans Algorithms Middle Aged Lung Diagnosis, Computer-Assisted Deep Learning Aged Adult Male Calibration Reference Standards Radiography, Thoracic Area Under Curve Bayes Theorem Pattern Recognition, Automated ROC Curve Image Processing, Computer-Assisted Predictive Value of Tests
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Investigating object compositionality in Generative Adversarial Networks.

Neural networks : the official journal of the International Neural Network Society Jul 13, 2020
Deep generative models seek to recover the process with which the observed data was generated. They may be used to synthesize new samples or to subsequently extract representations. Successful approaches in the domain of images are driven by several ...
Pattern Recognition, Automated Humans Neural Networks, Computer Image Processing, Computer-Assisted
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Analysis of the pattern recognition algorithm of broadband satellite modulation signal under deformable convolutional neural networks.

PloS one Jul 13, 2020
This research aims to analyze the effects of different parameter estimation on the recognition performance of satellite modulation signals based on deep learning (DL) under low signal to noise ratio (SNR) or channel non-ideal conditions. In this stud...
Satellite Communications Pattern Recognition, Automated Signal-To-Noise Ratio Neural Networks, Computer Deep Learning Signal Processing, Computer-Assisted
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Deep clustering with a Dynamic Autoencoder: From reconstruction towards centroids construction.

Neural networks : the official journal of the International Neural Network Society Jul 11, 2020
In unsupervised learning, there is no apparent straightforward cost function that can capture the significant factors of variations and similarities. Since natural systems have smooth dynamics, an opportunity is lost if an unsupervised objective func...
Cluster Analysis Pattern Recognition, Automated Algorithms Deep Learning
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Fast interactive medical image segmentation with weakly supervised deep learning method.

International journal of computer assisted radiology and surgery Jul 11, 2020
PURPOSE: To achieve accurate image segmentation, which is the first critical step in medical image analysis and interventions, using deep neural networks seems a promising approach provided sufficiently large and diverse annotated data from experts. ...
Echocardiography Diagnosis, Computer-Assisted Deep Learning Tomography, X-Ray Computed Reproducibility of Results Male Prostate Observer Variation Pattern Recognition, Automated Brachytherapy Ultrasonography Image Processing, Computer-Assisted Prostatic Neoplasms Humans Neural Networks, Computer Databases, Factual
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