2020 4th International Conference on Advanced Systems and Emergent Technologies (IC_ASET)最新文献_第4页

Design of a Novel Compact and Superdirective Two and Three Elements Antenna Array 一种新型紧凑型超指令二、三元天线阵列的设计

2020 4th International Conference on Advanced Systems and Emergent Technologies (IC_ASET) Pub Date : 2020-12-15 DOI: 10.1109/IC_ASET49463.2020.9318227

S. Dakhli, L. Laadhar, J. Floc'h, M. Sheikh, H. Rmili

引用次数: 0

Hybrid CNN-SVM classifier for efficient depression detection system 基于CNN-SVM混合分类器的高效凹陷检测系统

2020 4th International Conference on Advanced Systems and Emergent Technologies (IC_ASET) Pub Date : 2020-12-15 DOI: 10.1109/IC_ASET49463.2020.9318302

Afef Saidi, S. B. Othman, S. B. Saoud

{"title":"Hybrid CNN-SVM classifier for efficient depression detection system","authors":"Afef Saidi, S. B. Othman, S. B. Saoud","doi":"10.1109/IC_ASET49463.2020.9318302","DOIUrl":"https://doi.org/10.1109/IC_ASET49463.2020.9318302","url":null,"abstract":"Depression is a serious debilitating mental disorder affecting people from all ages all over the world. The number of depression cases increases annually in a continuous way. Due to the complexity of traditional techniques based on clinical diagnosis, there is a need for an automatic detection system of the depression. In this paper we present a novel audio-based approach to automatically detect depression using hybrid model. This model combines convolutional neural networks (CNN) and support vector machines (SVM), where SVM takes the place of the fully connected layers in CNN. In this proposed model, the features are automatically extracted using CNN and the classification is done using the SVM classifier. This approach was evaluated using DAIC-WOZ dataset provided by AVEC 2016 depression analysis sub-challenge. Experimental results showed that our hybrid model achieved an accuracy of 68% which outperform the CNN model (58.57%). Compared to the previous audio-based works using the same DAIC-WOZ dataset, our work showed a significant improvement in terms of accuracy, precision and recall.","PeriodicalId":250315,"journal":{"name":"2020 4th International Conference on Advanced Systems and Emergent Technologies (IC_ASET)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133264101","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: 28

Deep Learning for COVID-19 prediction 深度学习用于COVID-19预测

2020 4th International Conference on Advanced Systems and Emergent Technologies (IC_ASET) Pub Date : 2020-12-15 DOI: 10.1109/IC_ASET49463.2020.9318297

Safa Bahri, Moetez Kdayem, N. Zoghlami

引用次数: 6

Fire Tracking in Video Sequences Using Geometric Active Contours Controlled by Artificial Neural Network 基于人工神经网络控制的几何活动轮廓的视频序列火灾跟踪

2020 4th International Conference on Advanced Systems and Emergent Technologies (IC_ASET) Pub Date : 2020-12-15 DOI: 10.1109/IC_ASET49463.2020.9318289

A. Mouelhi, M. Bouchouicha, M. Sayadi, E. Moreau

{"title":"Fire Tracking in Video Sequences Using Geometric Active Contours Controlled by Artificial Neural Network","authors":"A. Mouelhi, M. Bouchouicha, M. Sayadi, E. Moreau","doi":"10.1109/IC_ASET49463.2020.9318289","DOIUrl":"https://doi.org/10.1109/IC_ASET49463.2020.9318289","url":null,"abstract":"Automatic fire and smoke detection is an important task to discover forest wildfires earlier. Tracking of smoke and fire in video sequences can provide helpful regional measures to evaluate precisely damages caused by fires. In security and surveillance applications, real-time video segmentation of both fire and smoke regions represents a crucial operation to avoid disaster. In this work, we propose a robust tracking method for fire regions using an artificial neural network (ANN) based approach combined with a hybrid geometric active contour (GAC) model based on Bayes error energy functional for forest wildfire videos. Firstly, an estimation function is built with local and global information collected from three color spaces (RGB, HIS and YCbCr) using Fisher's Linear Discriminant analysis (FLDA) and a trained ANN in order to get a preliminary fire pixel classification in each frame. This function is used to compute initial curves and the level set evolution parameters to control the active contour model providing a refined fire segmentation in each processed frame. The experimental results of the proposed tracking scheme proves its precision and robustness when tested on different varieties of scenarios whether wildfire-smoke video or outdoor fire sequences.","PeriodicalId":250315,"journal":{"name":"2020 4th International Conference on Advanced Systems and Emergent Technologies (IC_ASET)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133778407","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: 1

A novel method based on deep learning for herniated lumbar disc segmentation 基于深度学习的腰椎间盘突出症分割新方法

2020 4th International Conference on Advanced Systems and Emergent Technologies (IC_ASET) Pub Date : 2020-12-15 DOI: 10.1109/IC_ASET49463.2020.9318261

W. Mbarki, M. Bouchouicha, Sébastien Frizzi, Frederick Tshibasu, L. Ben Farhat, M. Sayadi

{"title":"A novel method based on deep learning for herniated lumbar disc segmentation","authors":"W. Mbarki, M. Bouchouicha, Sébastien Frizzi, Frederick Tshibasu, L. Ben Farhat, M. Sayadi","doi":"10.1109/IC_ASET49463.2020.9318261","DOIUrl":"https://doi.org/10.1109/IC_ASET49463.2020.9318261","url":null,"abstract":"Lower Back pain (LBP) is a common disease. Therefore, a common cause of leg pain and lower back is a lumbar disc herniation. Herniated lumbar disc represents a displacement of disc material (annulus fibrosis or nucleus pulpous). In most cases, the pain goes away within days to weeks; however, it can last for three months or more. Segmentation and Detection are the two most important tasks in computer aided diagnosis system (CAD) [24]. Extraction of herniated lumbar disc from magnetic (MRI) resonance imaging is a difficult task for radiologist. Detection of herniated disc was achieved by different methods such as region growing, active contours, watershed technique and thresholding. In our case, to detect intervertebral disc from lumbar MRI we developed an approach using convolutional neural networks in order to find the type of herniated lumbar disc [24] such as median, foraminal or post lateral [24]. We proposed to explore the importance of axial view MRI to find the type of herniation. Previous works were concentrated only on the sagittal View. The main objective of this paper is to automatically detect the intervertebral disc in magnetic resonance images(MRI) with bounding boxes and their classes which can facilitate diagnoses based on axial view MRI [40]. Therefore, the aim of this study is to assist detection using lumbar axial view MRI. A novel method is proposed in this paper based on deep convolutional neural networks. This study introduces the application of the convolutional neural network model. A framework was developed that enables the application of shape priors in the healthy part of intervertebral disc anatomy, with user intervention when the priors were inapplicable.","PeriodicalId":250315,"journal":{"name":"2020 4th International Conference on Advanced Systems and Emergent Technologies (IC_ASET)","volume":"242 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132593239","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

Trajectory Design and Tracking-Based Control of the Passive Compass Biped 被动罗经双足机器人轨迹设计与跟踪控制

2020 4th International Conference on Advanced Systems and Emergent Technologies (IC_ASET) Pub Date : 2020-12-15 DOI: 10.1109/IC_ASET49463.2020.9318277

Essia Added, H. Gritli

引用次数: 5

Characterization Of Reflection And Attenuation Parameters Of Device Under Test By VNA 用VNA表征被测器件的反射和衰减参数

2020 4th International Conference on Advanced Systems and Emergent Technologies (IC_ASET) Pub Date : 2020-12-15 DOI: 10.1109/IC_ASET49463.2020.9318263

N. Fezai, Fatima Zohra Hamdi Pacha, A. Amor

{"title":"Characterization Of Reflection And Attenuation Parameters Of Device Under Test By VNA","authors":"N. Fezai, Fatima Zohra Hamdi Pacha, A. Amor","doi":"10.1109/IC_ASET49463.2020.9318263","DOIUrl":"https://doi.org/10.1109/IC_ASET49463.2020.9318263","url":null,"abstract":"The calibration is defined by ISO/CEI 17025 “…set of operations that establish, under specified conditions, the relationship between values of quantities indicated by a measuring instrument or measuring system, or values represented by a material measure or a reference material, and the corresponding values realized by standards”. [2] [1] The term calibration is commonly used for the calibration of vector network analyzers (VNA) since it is impossible to directly measure the Sij parameters of any device. It is the role of the calibration to remove the parasitic contributions in order to keep only the contribution of the device under test (DUT). All the existing calibration methods therefore aim to determine the terms of systematic errors by given the matrix and complex nature of the measurand, the frequency range of various known standards. Indeed, the calibration then allows resetting the response of the instrument to a true predicted value calculated from the measured raw value. This correction made to the meter can then be seen as an improvement in its accuracy. So, the calibration of VNA insures the Traceability to SI for the reflection parameter. The topic of this paper is to present a method of calibration of VNA SOLT in order to quantify the terms of errors systematic and characterize the DUT by the resulting curves of the reflection and transmission factors of the DUT for a frequency range from 50 MHz to 20GHz, [2].","PeriodicalId":250315,"journal":{"name":"2020 4th International Conference on Advanced Systems and Emergent Technologies (IC_ASET)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125726199","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: 2

Performance Comparison Between Backstepping and P.I Regulators Methods For Four Level Flying Capacitor Inverter Based Active Power Filter Control 四电平飞容逆变器有源滤波控制中Backstepping与pi稳压方法的性能比较

2020 4th International Conference on Advanced Systems and Emergent Technologies (IC_ASET) Pub Date : 2020-12-15 DOI: 10.1109/IC_ASET49463.2020.9318314

L. Manai, Donia Hakiri, M. Besbes

引用次数: 0

Graphene patch array antenna at 60 GHz for 5G Millimeter-Wave Communications 用于5G毫米波通信的60 GHz石墨烯贴片阵列天线

2020 4th International Conference on Advanced Systems and Emergent Technologies (IC_ASET) Pub Date : 2020-12-15 DOI: 10.1109/IC_ASET49463.2020.9318309

Aymen Hlali, Z. Houaneb, H. Zairi

引用次数: 0

A simplified approach to a wheeled mobile robot control on uneven terrain 轮式移动机器人不平整地形控制的简化方法

2020 4th International Conference on Advanced Systems and Emergent Technologies (IC_ASET) Pub Date : 2020-12-15 DOI: 10.1109/IC_ASET49463.2020.9318279

Khouloud Balti, S. Elloumi

引用次数: 0