AIMC Topic: Pattern Recognition, Automated

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ClsGAN: Selective Attribute Editing Model based on Classification Adversarial Network.

Neural networks : the official journal of the International Neural Network Society Nov 10, 2020
Attribution editing has achieved remarkable progress in recent years owing to the encoder-decoder structure and generative adversarial network (GAN). However, it remains challenging to generate high-quality images with accurate attribute transformati...
Humans Neural Networks, Computer Pattern Recognition, Automated
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Adversarial symmetric GANs: Bridging adversarial samples and adversarial networks.

Neural networks : the official journal of the International Neural Network Society Nov 6, 2020
Generative adversarial networks have achieved remarkable performance on various tasks but suffer from training instability. Despite many training strategies proposed to improve training stability, this issue remains as a challenge. In this paper, we ...
Pattern Recognition, Automated Normal Distribution Image Processing, Computer-Assisted Unsupervised Machine Learning Humans Neural Networks, Computer
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Deep Learning-Based Segmentation and Quantification in Experimental Kidney Histopathology.

Journal of the American Society of Nephrology : JASN Nov 5, 2020
BACKGROUND: Nephropathologic analyses provide important outcomes-related data in experiments with the animal models that are essential for understanding kidney disease pathophysiology. Precision medicine increases the demand for quantitative, unbiase...
Neural Networks, Computer Male Diagnosis, Computer-Assisted Deep Learning Algorithms Reproducibility of Results Animals Kidney Diseases Kidney Glomerulus Translational Research, Biomedical Schiff Bases Pattern Recognition, Automated Periodic Acid Kidney Disease Models, Animal Mice, Inbred C57BL Image Processing, Computer-Assisted Mice
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Guided Attention Inference Network.

IEEE transactions on pattern analysis and machine intelligence Nov 3, 2020
With only coarse labels, weakly supervised learning typically uses top-down attention maps generated by back-propagating gradients as priors for tasks such as object localization and semantic segmentation. While these attention maps are intuitive and...
Supervised Machine Learning Neural Networks, Computer Image Processing, Computer-Assisted Semantics Pattern Recognition, Automated
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Sensor Fusion of Motion-Based Sign Language Interpretation with Deep Learning.

Sensors (Basel, Switzerland) Nov 2, 2020
Sign language was designed to allow hearing-impaired people to interact with others. Nonetheless, knowledge of sign language is uncommon in society, which leads to a communication barrier with the hearing-impaired community. Many studies of sign lang...
Gestures Sign Language Hand Humans Pattern Recognition, Automated Deep Learning
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Automatic Detection and Scoring of Kidney Stones on Noncontrast CT Images Using S.T.O.N.E. Nephrolithometry: Combined Deep Learning and Thresholding Methods.

Molecular imaging and biology Oct 27, 2020
PURPOSE: To develop and validate a deep learning and thresholding-based model for automatic kidney stone detection and scoring according to S.T.O.N.E. nephrolithometry.
Tomography, X-Ray Computed Female Pattern Recognition, Automated Aged Kidney Calculi Male Contrast Media Humans Middle Aged Algorithms Deep Learning Predictive Value of Tests Severity of Illness Index Retrospective Studies Imaging, Three-Dimensional Area Under Curve
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AutoTune: Automatically Tuning Convolutional Neural Networks for Improved Transfer Learning.

Neural networks : the official journal of the International Neural Network Society Oct 27, 2020
Transfer learning enables solving a specific task having limited data by using the pre-trained deep networks trained on large-scale datasets. Typically, while transferring the learned knowledge from source task to the target task, the last few layers...
Dogs Pattern Recognition, Automated Neural Networks, Computer Animals Machine Learning Bayes Theorem Databases, Factual
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Pattern Recognition of Spiking Neural Networks Based on Visual Mechanism and Supervised Synaptic Learning.

Neural plasticity Oct 27, 2020
Electrophysiological studies have shown that mammalian primary visual cortex are selective for the orientations of visual stimuli. Inspired by this mechanism, we propose a hierarchical spiking neural network (SNN) for image classification. Grayscale ...
Neurons Models, Neurological Synapses Humans Action Potentials Pattern Recognition, Automated Neural Networks, Computer Supervised Machine Learning
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Tumor segmentation in automated whole breast ultrasound using bidirectional LSTM neural network and attention mechanism.

Ultrasonics Oct 22, 2020
Accurate breast mass segmentation of automated breast ultrasound (ABUS) is a great help to breast cancer diagnosis and treatment. However, the lack of clear boundary and significant variation in mass shapes make the automatic segmentation very challe...
Image Interpretation, Computer-Assisted Pattern Recognition, Automated Humans Breast Neoplasms Neural Networks, Computer Diagnosis, Computer-Assisted Algorithms Ultrasonography, Mammary Female
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Predicting memory from study-related brain activity.

Journal of neurophysiology Oct 21, 2020
To isolate brain activity that may reflect effective cognitive processes during the study phase of a memory task, cognitive neuroscientists commonly contrast brain activity during study of later-remembered versus later-forgotten items. This "subseque...
Recognition, Psychology Cerebral Cortex Evoked Potentials Mental Recall Humans Electroencephalography Pattern Recognition, Automated Machine Learning Adult Functional Neuroimaging
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