Elsa Aniela Mendez Reguera,Mildred Lopez
Elsa Aniela Mendez Reguera
The COVID-19 pandemic transformed educational processes across different educational levels. As institutions and faculty members effort focused on guaranteeing academic continuity, the challenge was how to translate the learning methodologi...
A graph spatial-temporal model for predicting population density of key areas [0.03%]
关键区域人口密度预测的图时空模型
Zhihao Xu,Jianbo Li,Zhiqiang Lv et al.
Zhihao Xu et al.
Predicting the population density of key areas of the city is crucial. It helps reduce the spread risk of Covid-19 and predict individuals' travel needs. Although current researches focus on using the method of clustering to predict the pop...
Pablo A Vieira,Deborah M V Magalhães,Antonio O Carvalho-Filho et al.
Pablo A Vieira et al.
New and more transmissible SARS-COV-2 variants aggravated the SARS-COV-2 emergence. Lung X-ray images stand out as an alternative to support case screening. The latest computer-aided diagnosis systems have been using Deep Learning (DL) to d...
Nature-inspired solution for coronavirus disease detection and its impact on existing healthcare systems [0.03%]
受自然启发的冠状病毒疾病检测方法及其对现有医疗体系的影响
Kashif Naseer Qureshi,Adi Alhudhaif,Maria Ahmed Qureshi et al.
Kashif Naseer Qureshi et al.
Coronavirus is an infectious life-threatening disease and is mainly transmitted through infected person coughs, sneezes, or exhales. This disease is a global challenge that demands advanced solutions to address multiple dimensions of this p...
Prediction of COVID-19 - Pneumonia based on Selected Deep Features and One Class Kernel Extreme Learning Machine [0.03%]
基于选择的深度特征和一类核极小学习机的新型冠状病毒肺炎预测模型研究
Muhammad Attique Khan,Seifedine Kadry,Yu-Dong Zhang et al.
Muhammad Attique Khan et al.
In this work, we propose a deep learning framework for the classification of COVID-19 pneumonia infection from normal chest CT scans. In this regard, a 15-layered convolutional neural network architecture is developed which extracts deep fe...
Ahmad M Harb,Souhib M Harb
Ahmad M Harb
This paper presents a non-linear model to simulate and predict the spreading of the newly discovered disease caused by a new series of a Novel Coronavirus (COVID-19). The mathematical modeling in this study is based on the Susceptible Infec...
CNN Inference acceleration using low-power devices for human monitoring and security scenarios [0.03%]
用于人体监控和安全场景的低功耗设备CNN推理加速
Juan Mas,Teodoro Panadero,Guillermo Botella et al.
Juan Mas et al.
Security is currently one of the top concerns in our society. From governmental installations to private companies and medical institutions, they all have to address directly with security issues as: access to restricted information quarant...
Srinivas Koppu,Praveen Kumar Reddy Maddikunta,Gautam Srivastava
Srinivas Koppu
Deep learning applications with robotics contribute to massive challenges that are not addressed in machine learning. The present world is currently suffering from the COVID-19 pandemic, and millions of lives are getting affected every day ...
Data processing of 3D and 4D in-vivo electron paramagnetic resonance imaging co-registered with ultrasound. 3D printing as a registration tool [0.03%]
三维和四维活体电子顺磁共振成像与超声图像配准的数据处理。3D打印作为配准工具
M Gonet,B Epel,M Elas
M Gonet
We present the concept of image registration using ultrasound (US) and electron paramagnetic resonance (EPR) imaging and discuss the benefits of this solution, as well as its limitations. Both phantoms and murine tumors were used to test US...
Fast single image haze removal via local atmospheric light veil estimation [0.03%]
基于局部大气光照估值的快速去雾算法
Wei Sun,Hao Wang,Changhao Sun et al.
Wei Sun et al.
In this study, a novel single-image based dehazing framework is proposed to remove haze artifacts from images through local atmospheric light estimation. We use a novel strategy based on a physical model where the extreme intensity of each ...