AIMC Topic: Electronic Data Processing

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Unsupervised AER Object Recognition Based on Multiscale Spatio-Temporal Features and Spiking Neurons.

IEEE transactions on neural networks and learning systems Nov 30, 2020
This article proposes an unsupervised address event representation (AER) object recognition approach. The proposed approach consists of a novel multiscale spatio-temporal feature (MuST) representation of input AER events and a spiking neural network ...
Neural Networks, Computer Artificial Intelligence Algorithms Humans Neurons Pattern Recognition, Automated Electronic Data Processing Computer Simulation Models, Neurological Databases, Factual
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FMixCutMatch for semi-supervised deep learning.

Neural networks : the official journal of the International Neural Network Society Nov 10, 2020
Mixed sample augmentation (MSA) has witnessed great success in the research area of semi-supervised learning (SSL) and is performed by mixing two training samples as an augmentation strategy to effectively smooth the training space. Following the ins...
Databases, Factual Supervised Machine Learning Electronic Data Processing Deep Learning Entropy
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Automatic Gene Function Prediction in the 2020's.

Genes Oct 27, 2020
The current rate at which new DNA and protein sequences are being generated is too fast to experimentally discover the functions of those sequences, emphasizing the need for accurate Automatic Function Prediction (AFP) methods. AFP has been an active...
Proteins Models, Biological Amino Acid Sequence Algorithms Computational Biology Gene Ontology Electronic Data Processing Molecular Sequence Annotation Machine Learning
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Implementation of convolutional neural network approach for COVID-19 disease detection.

Physiological genomics Oct 23, 2020
In this paper, two novel, powerful, and robust convolutional neural network (CNN) architectures are designed and proposed for two different classification tasks using publicly available data sets. The first architecture is able to decide whether a gi...
Mass Chest X-Ray SARS-CoV-2 Data Accuracy Electronic Data Processing COVID-19 Humans Algorithms Neural Networks, Computer
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Deep neural networks enable quantitative movement analysis using single-camera videos.

Nature communications Aug 13, 2020
Many neurological and musculoskeletal diseases impair movement, which limits people's function and social participation. Quantitative assessment of motion is critical to medical decision-making but is currently possible only with expensive motion cap...
Male Walking Electronic Data Processing Gait Neural Networks, Computer Machine Learning Female Humans
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Automatic human identification from panoramic dental radiographs using the convolutional neural network.

Forensic science international Jul 15, 2020
Human identification is an important task in mass disaster and criminal investigations. Although several automatic dental identification systems have been proposed, accurate and fast identification from panoramic dental radiographs (PDRs) remains a c...
Humans Electronic Data Processing Radiography, Panoramic Forensic Dentistry Datasets as Topic Neural Networks, Computer Image Processing, Computer-Assisted
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Deep learning for genomics using Janggu.

Nature communications Jul 13, 2020
In recent years, numerous applications have demonstrated the potential of deep learning for an improved understanding of biological processes. However, most deep learning tools developed so far are designed to address a specific question on a fixed d...
Electronic Data Processing Humans Animals Genomics Computational Biology Deep Learning
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Missing Value Estimation Methods Research for Arrhythmia Classification Using the Modified Kernel Difference-Weighted KNN Algorithms.

BioMed research international Jun 21, 2020
Electrocardiogram (ECG) signal is critical to the classification of cardiac arrhythmia using some machine learning methods. In practice, the ECG datasets are usually with multiple missing values due to faults or distortion. Unfortunately, many establ...
Electronic Data Processing Models, Cardiovascular Computational Biology Electrocardiography Arrhythmias, Cardiac Humans Machine Learning
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DeLTA: Automated cell segmentation, tracking, and lineage reconstruction using deep learning.

PLoS computational biology Apr 13, 2020
Microscopy image analysis is a major bottleneck in quantification of single-cell microscopy data, typically requiring human oversight and curation, which limit both accuracy and throughput. To address this, we developed a deep learning-based image an...
Microfluidics Electronic Data Processing Cell Tracking Lab-On-A-Chip Devices Computational Biology Escherichia coli Microscopy, Fluorescence Single-Cell Analysis Image Processing, Computer-Assisted Software Algorithms Deep Learning
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Design a fluorometric aptasensor based on CoOOH nanosheets and carbon dots for simultaneous detection of lysozyme and adenosine triphosphate.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Feb 29, 2020
Simultaneous detection of biomarkers and biomolecules with great analytical performance still is challenging. A simple fluorometric dual-functional aptasensor was designed to detect Lysozyme (LYS) and adenosine triphosphate (ATP) as models of a prote...
Oxides Adenosine Triphosphate Cobalt Quantum Dots Spectrometry, Fluorescence Electronic Data Processing Muramidase Biosensing Techniques Support Vector Machine Aptamers, Nucleotide
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