AIMC Topic: Deep Learning

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Quantitative salivary gland SPECT/CT using deep convolutional neural networks.

Scientific reports
Quantitative single-photon emission computed tomography/computed tomography (SPECT/CT) using Tc-99m pertechnetate aids in evaluating salivary gland function. However, gland segmentation and quantitation of gland uptake is challenging. We develop a sa...

Improving protein domain classification for third-generation sequencing reads using deep learning.

BMC genomics
BACKGROUND: With the development of third-generation sequencing (TGS) technologies, people are able to obtain DNA sequences with lengths from 10s to 100s of kb. These long reads allow protein domain annotation without assembly, thus can produce impor...

Determinants of Tourism Stocks During the COVID-19: Evidence From the Deep Learning Models.

Frontiers in public health
This paper examines the determinants of tourism stock returns in China from October 25, 2018, to October 21, 2020, including the COVID-19 era. We propose four deep learning prediction models based on the Back Propagation Neural Network (BPNN): Quantu...

DL-MRI: A Unified Framework of Deep Learning-Based MRI Super Resolution.

Journal of healthcare engineering
Magnetic resonance imaging (MRI) is widely used in the detection and diagnosis of diseases. High-resolution MR images will help doctors to locate lesions and diagnose diseases. However, the acquisition of high-resolution MR images requires high magne...

A Deep Learning Approach for Table Tennis Forehand Stroke Evaluation System Using an IMU Sensor.

Computational intelligence and neuroscience
Psychological and behavioral evidence suggests that home sports activity reduces negative moods and anxiety during lockdown days of COVID-19. Low-cost, nonintrusive, and privacy-preserving smart virtual-coach Table Tennis training assistance could he...

Features Guided Face Super-Resolution via Hybrid Model of Deep Learning and Random Forests.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Face hallucination or super-resolution is a practical application of general image super-resolution which has been recently studied by many researchers. The challenge of good face hallucination comes from a variety of poses, illuminations, facial exp...

Generative Deep Learning in Digital Pathology Workflows.

The American journal of pathology
Many modern histopathology laboratories are in the process of digitizing their workflows. Digitization of tissue images has made it feasible to research the augmentation or automation of clinical reporting and diagnosis. The application of modern com...

Learning-based event locating for single-molecule force spectroscopy.

Biochemical and biophysical research communications
Acquiring events massively from single-molecule force spectroscopy (SMFS) experiments, which is crucial for revealing important biophysical information, is usually not straightforward. A significant amount of human labor is usually required to identi...

A new deep learning method for blood vessel segmentation in retinal images based on convolutional kernels and modified U-Net model.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Automatic monitoring of retinal blood vessels proves very useful for the clinical assessment of ocular vascular anomalies or retinopathies. This paper presents an efficient and accurate deep learning-based method for vessel ...