Adoption of improved neural network blade pattern recognition in prevention and control of corona virus disease-19 pandemic [0.03%]
改进神经网络叶片图案识别在预防和控制冠状病毒疾病2019大流行中的应用
Yanli Ma,Zhonghua Li,Jixiang Gou et al.
Yanli Ma et al.
To explore the adoption effect of improved neural network blade pattern in corona virus disease (COVID)-19, comparative analysis is implemented. First, the following hypotheses are proposed. I: in addition to the confirmed cases and deaths,...
Prediction on transmission trajectory of COVID-19 based on particle swarm algorithm [0.03%]
基于粒子群算法对COVID-19传播轨迹的预测研究
Caichang Ding,Yiqin Chen,Zhiyuan Liu et al.
Caichang Ding et al.
This study aimed to predict the transmission trajectory of the 2019 Corona Virus Disease (COVID-19). The particle swarm optimization (PSO) algorithm was combined with the traditional susceptible exposed infected recovered (SEIR) infectious ...
Mohammed Kutbi,Yizhe Chang,Philippos Mordohai
Mohammed Kutbi
We present an approach for motion clustering based on a novel observation that a signature for putative pixel correspondences can be generated by collecting their residuals with respect to model hypotheses drawn randomly from the data. Inli...
Intelligent computing on time-series data analysis and prediction of COVID-19 pandemics [0.03%]
基于时间序列数据的智能计算在新冠肺炎疫情分析与预测中的应用研究
Sujata Dash,Chinmay Chakraborty,Sourav K Giri et al.
Sujata Dash et al.
Covid-19 disease caused by novel coronavirus (SARS-CoV-2) is a highly contagious epidemic that originated in Wuhan, Hubei Province of China in late December 2019. World Health Organization (WHO) declared Covid-19 as a pandemic on 12th March...
MIDCAN: A multiple input deep convolutional attention network for Covid-19 diagnosis based on chest CT and chest X-ray [0.03%]
基于胸部CT和X射线的COVID-19诊断的多输入深度卷积注意力网络（ MIDCAN）
Yu-Dong Zhang,Zheng Zhang,Xin Zhang et al.
Yu-Dong Zhang et al.
Background: COVID-19 has caused 3.34m deaths till 13/May/2021. It is now still causing confirmed cases and ongoing deaths every day. Method: ...
Multi-region saliency-aware learning for cross-domain placenta image segmentation [0.03%]
用于跨域胎盘图像分割的多区域显著性感知学习
Zhuomin Zhang,Dolzodmaa Davaasuren,Chenyan Wu et al.
Zhuomin Zhang et al.
We propose a multi-region saliency-aware learning (MSL) method for cross-domain placenta image segmentation. Unlike most existing image-level transfer learning methods that fail to preserve the semantics of paired regions, our MSL incorpora...
A light CNN for detecting COVID-19 from CT scans of the chest [0.03%]
用于从胸部CT扫描中检测COVID-19的轻量级卷积神经网络
Matteo Polsinelli,Luigi Cinque,Giuseppe Placidi
Matteo Polsinelli
Computer Tomography (CT) imaging of the chest is a valid diagnosis tool to detect COVID-19 promptly and to control the spread of the disease. In this work we propose a light Convolutional Neural Network (CNN) design, based on the model of t...
COVID-CAPS: A capsule network-based framework for identification of COVID-19 cases from X-ray images [0.03%]
COVID-CAPS：一种基于胶囊网络的从X光图像中识别COVID-19病例的框架
Parnian Afshar,Shahin Heidarian,Farnoosh Naderkhani et al.
Parnian Afshar et al.
Novel Coronavirus disease (COVID-19) has abruptly and undoubtedly changed the world as we know it at the end of the 2nd decade of the 21st century. COVID-19 is extremely contagious and quickly spreading globally making its early diagnosis o...
Few-shot hypercolumn-based mitochondria segmentation in cardiac and outer hair cells in focused ion beam-scanning electron microscopy (FIB-SEM) data [0.03%]
基于少量样本超柱的聚焦离子束-扫描电子显微镜（FIB-SEM）数据中心细胞和外毛细胞中的线粒体分割技术研究
Julia Dietlmeier,Kevin McGuinness,Sandra Rugonyi et al.
Julia Dietlmeier et al.
We present a novel AI-based approach to the few-shot automated segmentation of mitochondria in large-scale electron microscopy images. Our framework leverages convolutional features from a pre-trained deep multilayer convolutional neural ne...
Semantics-enhanced supervised deep autoencoder for depth image-based 3D model retrieval [0.03%]
基于语义的监督深度自动编码器在深度图像中用于三维模型检索
Ayesha Siddiqua,Guoliang Fan
Ayesha Siddiqua
Increased accuracy and affordability of depth sensors such as Kinect has created a great depth-data source for various 3D oriented applications. Specifically, 3D model retrieval is attracting attention in the field of computer vision and pa...