AIMC Topic: Neural Networks, Computer

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Model-based convolutional neural network approach to underwater source-range estimation.

The Journal of the Acoustical Society of America Jan 1, 2021
This paper is part of a special issue on machine learning in acoustics. A model-based convolutional neural network (CNN) approach is presented to test the viability of this method as an alternative to conventional matched-field processing (MFP) for u...
Acoustics Deep Learning Image Processing, Computer-Assisted Neural Networks, Computer Machine Learning
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Highlighting interlanguage phoneme differences based on similarity matrices and convolutional neural network.

The Journal of the Acoustical Society of America Jan 1, 2021
The goal of this research is to find a way of highlighting the acoustic differences between consonant phonemes of the Polish and Lithuanian languages. For this purpose, similarity matrices are employed based on speech acoustic parameters combined wit...
Phonetics Neural Networks, Computer Support Vector Machine Language Acoustics
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Recent Progress of Deep Learning in Drug Discovery.

Current pharmaceutical design Jan 1, 2021
Deep learning, an emerging field of artificial intelligence based on neural networks in machine learning, has been applied in various fields and is highly valued. Herein, we mainly review several mainstream architectures in deep learning, including d...
Neural Networks, Computer Artificial Intelligence Drug Discovery Machine Learning Deep Learning Humans
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Ten computer codes that transformed science.

Nature Jan 1, 2021
Weather Programming Languages History, 21st Century National Library of Medicine (U.S.) Datasets as Topic Computational Biology United States Databases, Protein Deep Learning Time Factors Preprints as Topic Fourier Analysis History, 20th Century Physics Databases, Nucleic Acid Neural Networks, Computer Algorithms National Institutes of Health (U.S.) Databases, Factual
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Dual residual convolutional neural network (DRCNN) for low-dose CT imaging.

Journal of X-ray science and technology Jan 1, 2021
The excessive radiation doses in the application of computed tomography (CT) technology pose a threat to the health of patients. However, applying a low radiation dose in CT can result in severe artifacts and noise in the captured images, thus affect...
Artifacts Signal-To-Noise Ratio Humans Neural Networks, Computer Tomography, X-Ray Computed Image Processing, Computer-Assisted
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COVID-19 diagnosis from chest X-ray images using transfer learning: Enhanced performance by debiasing dataloader.

Journal of X-ray science and technology Jan 1, 2021
BACKGROUND: Chest X-ray imaging has been proved as a powerful diagnostic method to detect and diagnose COVID-19 cases due to its easy accessibility, lower cost and rapid imaging time.
Early Diagnosis Radiography, Thoracic Deep Learning Pneumonia COVID-19 Algorithms Reproducibility of Results SARS-CoV-2 Tomography, X-Ray Computed Humans Neural Networks, Computer
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Domain adaptation for robust workload level alignment between sessions and subjects using fNIRS.

Journal of biomedical optics Jan 1, 2021
SIGNIFICANCE: We demonstrated the potential of using domain adaptation on functional near-infrared spectroscopy (fNIRS) data to classify different levels of n-back tasks that involve working memory.
Humans Support Vector Machine Memory, Short-Term Neural Networks, Computer Spectroscopy, Near-Infrared
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Application of convolution neural network in medical image processing.

Technology and health care : official journal of the European Society for Engineering and Medicine Jan 1, 2021
BACKGROUND: Convolution neural network is often superior to other similar algorithms in image classification. Convolution layer and sub-sampling layer have the function of extracting sample features, and the feature of sharing weights greatly reduces...
Humans Image Processing, Computer-Assisted Neural Networks, Computer Algorithms
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Intelligent medical image feature extraction method based on improved deep learning.

Technology and health care : official journal of the European Society for Engineering and Medicine Jan 1, 2021
BACKGROUND: Medical patients can be diagnosed early, however it is difficult to extract effective features in medical image segmentation based on semantic information.
Machine Learning Image Processing, Computer-Assisted Humans Brain Neoplasms Neural Networks, Computer Deep Learning
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Improved SSD network for accurate detection of optic disc and fovea and application in excyclotropia screening.

Journal of the Optical Society of America. A, Optics, image science, and vision Jan 1, 2021
The detection of the optic disc (OD) and fovea is essential to many automatic diagnosis systems for retinal diseases. The single shot multibox detector (SSD) can generate predictions from feature maps of various resolutions, which has not been introd...
Databases, Factual Humans Pattern Recognition, Automated Fovea Centralis Image Interpretation, Computer-Assisted Reproducibility of Results Exotropia Optic Disk Sensitivity and Specificity Neural Networks, Computer Algorithms
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