2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH)最新文献_第2页

A Comparative Study of Deep Learning Networks for COVID-19 Recognition in Chest X-ray Images 深度学习网络在胸部x线图像中识别COVID-19的比较研究

2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH) Pub Date : 2021-02-09 DOI: 10.1109/IHSH51661.2021.9378703

Sabrina Nefoussi, Abdenour Amamra, Idir Amine Amarouche

{"title":"A Comparative Study of Deep Learning Networks for COVID-19 Recognition in Chest X-ray Images","authors":"Sabrina Nefoussi, Abdenour Amamra, Idir Amine Amarouche","doi":"10.1109/IHSH51661.2021.9378703","DOIUrl":"https://doi.org/10.1109/IHSH51661.2021.9378703","url":null,"abstract":"The COVID-19 pandemic is devastatingly affecting the health and well-being of the worldwide population. A basic advance in the battle against it resides in effective screening of infected patients, with one of the key screening approaches such as radiological imaging based on chest radiography. Faced with this challenge, various artificial intelligence (AI) frameworks, mostly based on deep learning, have been proposed and results have been getting better and very promising as the precision of positive cases recognition is constantly refined. In the light of previous work on automated X-ray image screening, we train several deep convolutional networks for the classification of chest pathologies into: normal, pneumonia, and COVID-19. We use three open-source and one private dataset for the validation of our findings. Unfortunately, data scarcity remains a big challenge hurdling COVID-19 automatic recognition research. In our case, we used a total of 518 COVID-19 positive X-ray images. We evaluate different architectures for COVID-19 recognition with different deep neural architecture.","PeriodicalId":127735,"journal":{"name":"2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH)","volume":"138 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116854063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

A Model Stacking Approach for Ride-Hailing Demand Forecasting : a Case Study of Algiers 网约车需求预测的模型叠加方法:以阿尔及尔市为例

2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH) Pub Date : 2021-02-09 DOI: 10.1109/IHSH51661.2021.9378731

Soumia Boumeddane, Leila Hamdad, Abdelkader Abou El-Feda Bouregag, Miloud Damene, Souhila Sadeg

引用次数: 1

A summary of the existing challenges in the design of a routing protocol in UAVs network 总结了无人机网络路由协议设计中存在的问题

2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH) Pub Date : 2021-02-09 DOI: 10.1109/IHSH51661.2021.9378729

Boutalbi Mohammed Chaker, Riahla Mohamed Amine, Ahriche Aimad

引用次数: 3

Heuristic and learning method for obstacle avoidance with mobile robot 移动机器人避障的启发式学习方法

2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH) Pub Date : 2021-02-09 DOI: 10.1109/IHSH51661.2021.9378725

F. Lachekhab, D. Acheli, M. Tadjine, Yassine Meraihi

引用次数: 1

Human Age And Gender Classification using Convolutional Neural Network 基于卷积神经网络的人类年龄和性别分类

2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH) Pub Date : 2021-02-09 DOI: 10.1109/IHSH51661.2021.9378708

Mohammed Kamel Benkaddour, Sara Lahlali, Maroua Trabelsi

引用次数: 13

Deep Learning-Based Sentiment Analysis of Algerian Dialect during Hirak 2019 基于深度学习的Hirak阿尔及利亚方言情感分析

2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH) Pub Date : 2021-02-09 DOI: 10.1109/IHSH51661.2021.9378753

A. Mazari, Abdelhamid Djeffal

{"title":"Deep Learning-Based Sentiment Analysis of Algerian Dialect during Hirak 2019","authors":"A. Mazari, Abdelhamid Djeffal","doi":"10.1109/IHSH51661.2021.9378753","DOIUrl":"https://doi.org/10.1109/IHSH51661.2021.9378753","url":null,"abstract":"Recent studies have used sentiment classification to analyze social media content using either semantic rule-based methods such as linguistic extraction models obtained from morpho-syntactic analysis, statistical methods based on Bag-of-word techniques or machine learning and deep learning models. This work uses the traditional Machine Learning algorithms and the Deep Learning models (Convolutional Neural Networks CNN and Recurrent Neural Networks RNN) applying on corpus collected from social media (Facebook, YouTube and Twitter) about the Hirak_19 (popular protest in Algeria during 2019) written in Algerian Dialect to analyze sentiments and provide a deeper understanding of opinions. The corpus is built from several dialectal Arabic texts; it consists of 7800 comments about political Hirak topics. CNN and RNN have been applied in several applications; in this paper, we show their power of detecting and classifying opinions about a social issue and analyzing sentiments. The results are positive demonstrated by the accuracy scheme 63.28% (CNN) and 60.97 (RNN) of cross-validation tests.","PeriodicalId":127735,"journal":{"name":"2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116464477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

M-Health Application for Managing a Patient's Medical Record based on the Cloud: Design and Implementation 基于云管理患者病历的移动健康应用:设计与实现

2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH) Pub Date : 2021-02-09 DOI: 10.1109/IHSH51661.2021.9378744

Sihem Souiki, M. Hadjila, Djillali Moussaoui, Soria Ferdi, Soumia Rais

{"title":"M-Health Application for Managing a Patient's Medical Record based on the Cloud: Design and Implementation","authors":"Sihem Souiki, M. Hadjila, Djillali Moussaoui, Soria Ferdi, Soumia Rais","doi":"10.1109/IHSH51661.2021.9378744","DOIUrl":"https://doi.org/10.1109/IHSH51661.2021.9378744","url":null,"abstract":"Mobile health (MH) technologies and electronic medical record represent a powerful solution which can help both patients and doctors in daily health monitoring and treatment, especially for patient's leaves in rural areas. In this context, we propose to design and build a mobile application for the management of a patient's medical data on the Cloud. In this paper, we define the medical record in a comprehensive manner and then present the mobile applications as well as the mobile operating system used, the Android system. The proposed work is composed of two parts; firstly, we choose UML formalism to model our application. Our choice was based on its simplicity, performance and design readiness. Secondly, in order to achieve this mobile application, we used the Java programming language under the Android Studio development environment, and when implementing our application's data storage space, we used XML for data structure and Cloud Computing as a storage space for its security and to protect the patient's privacy.","PeriodicalId":127735,"journal":{"name":"2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129336960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Facial Expression Recognition using Locally Linear Embedding with LBP and HOG Descriptors 基于LBP和HOG描述符的局部线性嵌入人脸表情识别

2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH) Pub Date : 2021-02-09 DOI: 10.1109/IHSH51661.2021.9378702

Yacine Yaddaden, Mehdi Adda, A. Bouzouane

{"title":"Facial Expression Recognition using Locally Linear Embedding with LBP and HOG Descriptors","authors":"Yacine Yaddaden, Mehdi Adda, A. Bouzouane","doi":"10.1109/IHSH51661.2021.9378702","DOIUrl":"https://doi.org/10.1109/IHSH51661.2021.9378702","url":null,"abstract":"Facial expression recognition intervenes in various fields of applications such as human-computer interaction. Despite the fact that several methods are regularly proposed, designing an efficient automatic facial expression recognition method remains challenging. In this paper, we propose a method through which we compare the performance of two common and well-known image descriptors namely Local Binary Patterns and Histogram of Oriented Gradients. Both are used by two distinct manners; global which uses the whole face while the local exploits predefined sub-regions. Moreover, we employ a specific dimensionality reduction technique namely Locally Linear Embedding. As for the recognition part, we choose to employ a multiclass Support Vector Machine classifier for its generalization capabilities in order to recognize the expressed emotion among the six basic ones. Finally, we assess the performances of the proposed method using three different and common datasets namely KDEF, JAFFE and RafD. The obtained results are promising with corresponding recognition rates; 85.48%, 96.05% and 93.54%, respectively.","PeriodicalId":127735,"journal":{"name":"2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130045647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Transfer Learning for Automatic Brain Tumor Classification Using MRI Images 基于MRI图像的脑肿瘤自动分类迁移学习

2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH) Pub Date : 2021-02-09 DOI: 10.1109/IHSH51661.2021.9378739

Mohamed Arbane, R. Benlamri, Youcef Brik, Mohamed Djerioui

引用次数: 23

Attitude Determination and Attitude Estimation in Aircraft and Spacecraft Navigation. A survey 飞行器和航天器导航中的姿态确定和姿态估计。一项调查显示

2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH) Pub Date : 2021-02-09 DOI: 10.1109/IHSH51661.2021.9378714

Djamel Dhahbane, A. Nemra, S. Sakhi

{"title":"Attitude Determination and Attitude Estimation in Aircraft and Spacecraft Navigation. A survey","authors":"Djamel Dhahbane, A. Nemra, S. Sakhi","doi":"10.1109/IHSH51661.2021.9378714","DOIUrl":"https://doi.org/10.1109/IHSH51661.2021.9378714","url":null,"abstract":"In the domain of Engennering, especially in GNC (Guidance, Navigation, Control), attitude can be defined as the orientation of a body frame in 3D space with respect to another frame called “reference frame”. Have information obout this orientation is very prominent to achieve high reliability of the system in question. This paper adresses the concept attitude determination and attitude estimation of body in motion (aircraft and spacecraft). It summarizes many published reasercher's works that exists in the literature, and which treat the main notions in this field. It is about forms of attitude representation, diference between the two famous principal branches: attitude determination and attitude estimation. After that, different sensors and approaches used in each branch are outlined in chronological order. A detail description of these sensors and algorithms are given. Simulation results of attitude determination are illustrated. This brief also represents an overview which may help readers and developpers to more understand the subject of attitude representation and attitude sensors. It allows them to master the attitude determination and attitude estimation in aircraft and spacecraft navigation.","PeriodicalId":127735,"journal":{"name":"2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130920303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5