AIMC Topic: Computers

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tinyHLS: a novel open source high level synthesis tool targeting hardware accelerators for artificial neural network inference.

Physiological measurement
In recent years, wearable devices such as smartwatches and smart patches have revolutionized biosignal acquisition and analysis, particularly for monitoring electrocardiography (ECG). However, the limited power supply of these devices often precludes...

Neuromorphic computing at scale.

Nature
Neuromorphic computing is a brain-inspired approach to hardware and algorithm design that efficiently realizes artificial neural networks. Neuromorphic designers apply the principles of biointelligence discovered by neuroscientists to design efficien...

On energy complexity of fully-connected layers.

Neural networks : the official journal of the International Neural Network Society
The massive increase in the size of deep neural networks (DNNs) is accompanied by a significant increase in energy consumption of their hardware implementations which is critical for their widespread deployment in low-power mobile devices. In our pre...

Neuromorphic one-shot learning utilizing a phase-transition material.

Proceedings of the National Academy of Sciences of the United States of America
Design of hardware based on biological principles of neuronal computation and plasticity in the brain is a leading approach to realizing energy- and sample-efficient AI and learning machines. An important factor in selection of the hardware building ...

A novel activation function based on DNA enzyme-free hybridization reaction and its implementation on nonlinear molecular learning systems.

Physical chemistry chemical physics : PCCP
With the advent of the post-Moore's Law era, the development of traditional silicon-based computers has reached its limit, and there is an urgent need to develop new computing technologies to meet the needs of science, technology, and daily life. Due...

Eye-LRCN: A Long-Term Recurrent Convolutional Network for Eye Blink Completeness Detection.

IEEE transactions on neural networks and learning systems
Computer vision syndrome causes vision problems and discomfort mainly due to dry eye. Several studies show that dry eye in computer users is caused by a reduction in the blink rate and an increase in the prevalence of incomplete blinks. In this conte...

Slideflow: deep learning for digital histopathology with real-time whole-slide visualization.

BMC bioinformatics
Deep learning methods have emerged as powerful tools for analyzing histopathological images, but current methods are often specialized for specific domains and software environments, and few open-source options exist for deploying models in an intera...

A Computer Vision-Based System to Help Health Professionals to Apply Tests for Fall Risk Assessment.

Sensors (Basel, Switzerland)
The increase in life expectancy, and the consequent growth of the elderly population, represents a major challenge to guarantee adequate health and social care. The proposed system aims to provide a tool that automates the evaluation of gait and bala...

IODeep: An IOD for the introduction of deep learning in the DICOM standard.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: In recent years, Artificial Intelligence (AI) and in particular Deep Neural Networks (DNN) became a relevant research topic in biomedical image segmentation due to the availability of more and more data sets along with the e...

Comparison of clinical geneticist and computer visual attention in assessing genetic conditions.

PLoS genetics
Artificial intelligence (AI) for facial diagnostics is increasingly used in the genetics clinic to evaluate patients with potential genetic conditions. Current approaches focus on one type of AI called Deep Learning (DL). While DL- based facial diagn...