October 2020

Deriving A Novel Health Index Using A Large-Scale Population Based Electronic Health RecordWith Deep Networks

Deriving A Novel Health Index Using A Large-Scale Population Based Electronic Health Record With Deep Networks

Abstract Health indexes are useful tools for monitoring the health condition of a population and can be used to guide the healthcare policy of governments. However, most health indexes are […]

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Corona Discharge-Induced WaterDroplet Growth in Air

Corona Discharge-Induced WaterDroplet Growth in Air

Abstract In natural clouds, water droplets grow by condensation in a supersaturated environment. Under subsaturatedconditions, water droplets normally keep evaporating until they eventually disappear. In this article, we study the

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UNIVERSAL MULTI-MODAL DEEP NETWORK FOR CLASSIFICATION AND SEGMENTATION OF MEDICAL IMAGES

Universal multi-modal deep network for classification and segmentation of medical images

Abstract Medical image processing algorithms have traditionally focused on a specific problem or disease per modality. This approach has continued with the wide-spread adoption of deep learning in the last

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Object-Oriented (oop) Design of the Specialized Software for Automation of the Metallographic Analysis

Object-oriented (oop) design of the Specialized Software for Automation of the Metallographic Analysis

Abstract The relevance to developing the specialized software for automation of the metallographic analysis has been substantiated. The object model of the specialized software for automation of the metallographic analysis

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Integrated Pico-Tesla Resolution Magnetoresistive Sensors for Miniaturised Magnetomyography(MMG)

Integrated Pico-Tesla Resolution Magnetoresistive Sensors for Miniaturised Magnetomyography (MMG)

Abstract Magnetomyography (MMG) is the measurement of magnetic signals generated in the skeletal muscle of humans by electrical activities. However, current technologies developed to detect such a tiny magnetic field

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Wildfire Segmentation on Satellite Images using Deep Learning

Wildfire Segmentation on Satellite Images using Deep Learning

Abstract Deep learning and convolutional neural network technologies are increasingly used in the problems of analysis, segmentation, and recognition of objects in images. In this article, a convolutional neural network

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DEEP LEARNING BASED SEGMENTATION OF BODY PARTS IN CT LOCALIZERS ANDAPPLICATION TO SCAN PLANNING

Deep Learning Based Segmentation of Body Parts in CT Localizers and Application to Scan Planning

Abstract in this paper, we propose a deep learning approach for the segmentation of body parts in computer tomography (CT) localizer images. Such images pose dif[1]culties in the automatic image

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A Rapid, Accurate and Machine-Agnostic Segmentation and Quantification Method for CT-Based COVID-19 Diagnosis

A Rapid, Accurate and Machine-Agnostic Segmentation and Quantification Method for CT-Based COVID-19 Diagnosis

Abstract COVID-19 has caused a global pandemic and become the most urgent threat to the entire world. Tremendous efforts and resources have been invested in developing diagnosis, prognosis and treatment

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Work-in-Progress—The Sudden Requirement to Work from Home Due to COVID-19 Pandemic Restrictions: Attitudes and Changes in Perceived Value of Physical and Immersive Workspaces —

Work-in-Progress—The Sudden Requirement to Work from Home Due to COVID-19 Pandemic Restrictions: Attitudes and Changes in Perceived Value of Physical and Immersive Workspaces

Abstract What begins as an undifferentiated space becomes a place as we get to know it better and endow it with value, space is freedom [1]. The context for this

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