AIMC Topic: Deep Learning

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A method for the automatic detection of myopia in Optos fundus images based on deep learning.

International journal for numerical methods in biomedical engineering
Myopia detection is significant for preventing irreversible visual impairment and diagnosing myopic retinopathy. To improve the detection efficiency and accuracy, a Myopia Detection Network (MDNet) that combines the advantages of dense connection and...

Classification of Skin Disease Using Deep Learning Neural Networks with MobileNet V2 and LSTM.

Sensors (Basel, Switzerland)
Deep learning models are efficient in learning the features that assist in understanding complex patterns precisely. This study proposed a computerized process of classifying skin disease through deep learning based MobileNet V2 and Long Short Term M...

Neural network approximation: Three hidden layers are enough.

Neural networks : the official journal of the International Neural Network Society
A three-hidden-layer neural network with super approximation power is introduced. This network is built with the floor function (⌊x⌋), the exponential function (2), the step function (1), or their compositions as the activation function in each neuro...

Using a Deep Learning Method and Data from Two-Dimensional (2D) Marker-Less Video-Based Images for Walking Speed Classification.

Sensors (Basel, Switzerland)
Human body measurement data related to walking can characterize functional movement and thereby become an important tool for health assessment. Single-camera-captured two-dimensional (2D) image sequences of marker-less walking individuals might be a ...

Facial Emotions Are Accurately Encoded in the Neural Signal of Those With Autism Spectrum Disorder: A Deep Learning Approach.

Biological psychiatry. Cognitive neuroscience and neuroimaging
BACKGROUND: Individuals with autism spectrum disorder (ASD) exhibit frequent behavioral deficits in facial emotion recognition (FER). It remains unknown whether these deficits arise because facial emotion information is not encoded in their neural si...

A deep-learning-based workflow to assess taxonomic affinity of hominid teeth with a test on discriminating Pongo and Homo upper molars.

American journal of physical anthropology
OBJECTIVES: Convolutional neural network (CNN) is a state-of-art deep learning (DL) method with superior performance in image classification. Here, a CNN-based workflow is proposed to discriminate hominid teeth. Our hope is that this method could hel...

A hybrid deep learning approach for gland segmentation in prostate histopathological images.

Artificial intelligence in medicine
BACKGROUND: In digital pathology, the morphology and architecture of prostate glands have been routinely adopted by pathologists to evaluate the presence of cancer tissue. The manual annotations are operator-dependent, error-prone and time-consuming....

Deep learning to segment pelvic bones: large-scale CT datasets and baseline models.

International journal of computer assisted radiology and surgery
PURPOSE: Pelvic bone segmentation in CT has always been an essential step in clinical diagnosis and surgery planning of pelvic bone diseases. Existing methods for pelvic bone segmentation are either hand-crafted or semi-automatic and achieve limited ...