Pub Date : 2020-06-01DOI: 10.1109/ISCV49265.2020.9204316
A. Daoui, H. Karmouni, Ayoub Azzayani, M. Sayyouri, H. Qjidaa
In this paper, we propose a new type of hybrid discrete orthogonal moments called the Tchebichef-Charlier (TC) moments. This type of moment is created on the basis of the Tchebichef and Charlier polynomials in order to exploit the important properties of each one of these polynomials. This paper also suggests a new fast method for the reconstruction of the large-size 1D signal. This proposed method requires the signal conversion from 1D to 2D space and then the use of matrix formulations for the reconstruction in the 2D space. The simulations performed clearly show the usefulness of the proposed hybrid TC moments for the reconstruction and for the localization of regions of interest (ROI) of a large-size 1D signal.
{"title":"Large Size 1D Signal Analysis by Hybrid Tchebichef-Charlier Moments","authors":"A. Daoui, H. Karmouni, Ayoub Azzayani, M. Sayyouri, H. Qjidaa","doi":"10.1109/ISCV49265.2020.9204316","DOIUrl":"https://doi.org/10.1109/ISCV49265.2020.9204316","url":null,"abstract":"In this paper, we propose a new type of hybrid discrete orthogonal moments called the Tchebichef-Charlier (TC) moments. This type of moment is created on the basis of the Tchebichef and Charlier polynomials in order to exploit the important properties of each one of these polynomials. This paper also suggests a new fast method for the reconstruction of the large-size 1D signal. This proposed method requires the signal conversion from 1D to 2D space and then the use of matrix formulations for the reconstruction in the 2D space. The simulations performed clearly show the usefulness of the proposed hybrid TC moments for the reconstruction and for the localization of regions of interest (ROI) of a large-size 1D signal.","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132433750","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}
Pub Date : 2020-06-01DOI: 10.1109/ISCV49265.2020.9204142
Zakaria Kaddari, Youssef Mellah, Jamal Berrich, T. Bouchentouf, M. Belkasmi
In this paper, we present the work we did on the MCTACO dataset, which is concerned with temporal common sense understanding in natural language processing. We begin by describing our approach that we called T5NCSU (T5 Normalization Common Sense Understanding), which relies on preprocessing techniques like duration units normalization and the use of the recently released T5 text-to-text pre-trained language model, we then present and discuss our results. Using our approach we were able to obtain the state-of-the-art on the MCTACO dataset leaderboard.
{"title":"Applying the T5 language model and duration units normalization to address temporal common sense understanding on the MCTACO dataset","authors":"Zakaria Kaddari, Youssef Mellah, Jamal Berrich, T. Bouchentouf, M. Belkasmi","doi":"10.1109/ISCV49265.2020.9204142","DOIUrl":"https://doi.org/10.1109/ISCV49265.2020.9204142","url":null,"abstract":"In this paper, we present the work we did on the MCTACO dataset, which is concerned with temporal common sense understanding in natural language processing. We begin by describing our approach that we called T5NCSU (T5 Normalization Common Sense Understanding), which relies on preprocessing techniques like duration units normalization and the use of the recently released T5 text-to-text pre-trained language model, we then present and discuss our results. Using our approach we were able to obtain the state-of-the-art on the MCTACO dataset leaderboard.","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121953168","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}
Pub Date : 2020-06-01DOI: 10.1109/ISCV49265.2020.9204309
Virik Jain, Jash Lodhavia
Stack Overflow is one of the most widely used platforms for asking questions and queries on topics related to computer science, software development and general computer programming. Tagging of the questions is particularly useful for indexing information based on the tags. Currently, a user enters the tag manually for a question asked by him/her. The question should contain at least one tag manually typed by the user. It can be seen that most of the questions asked should either have more tags associated with it or aren’t tagged accurately and appropriately. Since there are a huge number of tags, the process of searching through all the tags manually and find relevant ones can be cumbersome and is therefore overlooked by most of the users asking the questions. This research is focused on exploring methods for developing an autonomous tagging system using Machine learning methods like k-Nearest Neighbors and Random Forest along with some crucial data preprocessing steps like Stemming, Tokenization and removing Stop words. The dataset for the above research is taken from kaggle.com which has a 10% Stackoverflow question dataset open for all. The results of the following proposed system for automatic tagging were satisfactory. Random Forest gave an average percentage accuracy of 70% across all the tags while k-Nearest Neighbors performed slightly better giving an accuracy of 75%.
{"title":"Automatic Question Tagging using k-Nearest Neighbors and Random Forest","authors":"Virik Jain, Jash Lodhavia","doi":"10.1109/ISCV49265.2020.9204309","DOIUrl":"https://doi.org/10.1109/ISCV49265.2020.9204309","url":null,"abstract":"Stack Overflow is one of the most widely used platforms for asking questions and queries on topics related to computer science, software development and general computer programming. Tagging of the questions is particularly useful for indexing information based on the tags. Currently, a user enters the tag manually for a question asked by him/her. The question should contain at least one tag manually typed by the user. It can be seen that most of the questions asked should either have more tags associated with it or aren’t tagged accurately and appropriately. Since there are a huge number of tags, the process of searching through all the tags manually and find relevant ones can be cumbersome and is therefore overlooked by most of the users asking the questions. This research is focused on exploring methods for developing an autonomous tagging system using Machine learning methods like k-Nearest Neighbors and Random Forest along with some crucial data preprocessing steps like Stemming, Tokenization and removing Stop words. The dataset for the above research is taken from kaggle.com which has a 10% Stackoverflow question dataset open for all. The results of the following proposed system for automatic tagging were satisfactory. Random Forest gave an average percentage accuracy of 70% across all the tags while k-Nearest Neighbors performed slightly better giving an accuracy of 75%.","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117237273","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}
Pub Date : 2020-06-01DOI: 10.1109/ISCV49265.2020.9204114
M. Z. Amrani, C. Borst, N. Achour
This paper presents hand gesture classification using fuzzy logic, with an application to the Rock-Paper-Scissors game. It includes a comparison between a simple threshold classifier and the Fuzzy Logic classifier. The real-time gesture recognition is implemented for the Leap Motion input device. Although the human’s game gesture pattern may seem random, some recent work suggests how it is possible to predict an opponent’s gesture, from a previous gesture, with better-than-random success. Based on this, we designed a conditional-response algorithm making the behavior of the virtual player more similar to a real human. Using networking tools, we enable game play remotely against other players. The game was experimentally evaluated with eleven players, reaching an average online classification accuracy of 97.35% for hand pattern recognition. The evaluation metrics are represented in confusion matrices.
{"title":"Fuzzy Logic Classifier and Conditional Responses Algorithm for Gestural Input Game","authors":"M. Z. Amrani, C. Borst, N. Achour","doi":"10.1109/ISCV49265.2020.9204114","DOIUrl":"https://doi.org/10.1109/ISCV49265.2020.9204114","url":null,"abstract":"This paper presents hand gesture classification using fuzzy logic, with an application to the Rock-Paper-Scissors game. It includes a comparison between a simple threshold classifier and the Fuzzy Logic classifier. The real-time gesture recognition is implemented for the Leap Motion input device. Although the human’s game gesture pattern may seem random, some recent work suggests how it is possible to predict an opponent’s gesture, from a previous gesture, with better-than-random success. Based on this, we designed a conditional-response algorithm making the behavior of the virtual player more similar to a real human. Using networking tools, we enable game play remotely against other players. The game was experimentally evaluated with eleven players, reaching an average online classification accuracy of 97.35% for hand pattern recognition. The evaluation metrics are represented in confusion matrices.","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126175001","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}
Pub Date : 2020-06-01DOI: 10.1109/ISCV49265.2020.9204326
I. E. Kadmiri, F. Elamri, Y. Ben-Ali, A. Khaled, Abdelhamid Kerkour-El Miad, D. Bria
In our actual work, we investigate the propagation of acoustic/elastic waves in a periodic structure consisting of a segment of length d1 and two asymmetric loops of lengths d2 and d3 in each cellule of the periodic structure. The perfect periodic structure presents wide pass bands separated by wide forbidden bands (the propagation of the acoustic waves is prohibited). These band gaps come from the periodicity of the system and the localized modes of the loops. The width of these bands is sensitive to the length of the guide as well as the number of N sites. The presence of a defect on the guide (segment) inside this structure can create defect modes within forbidden bands. These localized states are sensitive to the lengths of the two loops, the periodicity of the structure, and the length of the defected guide. We see that the number of defect modes inside the band gap increases progressively from low to high frequencies with the variation of the defect guide. This structure can also be used as high performance and high transmittance acoustic filters when a defect guide is created into the finite periodic system. Our theoretical is carried out using the continuous medium interface response theory, which makes it possible to calculate the Green function of any composite material. This allows us to obtain all the physical properties of the periodic structure studied, in particular, the dispersion relation and the transmission coefficient.
{"title":"Induced guided acoustic waves by the presence of a defective guide in one dimensional asymmetric loop phononic crystal","authors":"I. E. Kadmiri, F. Elamri, Y. Ben-Ali, A. Khaled, Abdelhamid Kerkour-El Miad, D. Bria","doi":"10.1109/ISCV49265.2020.9204326","DOIUrl":"https://doi.org/10.1109/ISCV49265.2020.9204326","url":null,"abstract":"In our actual work, we investigate the propagation of acoustic/elastic waves in a periodic structure consisting of a segment of length d1 and two asymmetric loops of lengths d2 and d3 in each cellule of the periodic structure. The perfect periodic structure presents wide pass bands separated by wide forbidden bands (the propagation of the acoustic waves is prohibited). These band gaps come from the periodicity of the system and the localized modes of the loops. The width of these bands is sensitive to the length of the guide as well as the number of N sites. The presence of a defect on the guide (segment) inside this structure can create defect modes within forbidden bands. These localized states are sensitive to the lengths of the two loops, the periodicity of the structure, and the length of the defected guide. We see that the number of defect modes inside the band gap increases progressively from low to high frequencies with the variation of the defect guide. This structure can also be used as high performance and high transmittance acoustic filters when a defect guide is created into the finite periodic system. Our theoretical is carried out using the continuous medium interface response theory, which makes it possible to calculate the Green function of any composite material. This allows us to obtain all the physical properties of the periodic structure studied, in particular, the dispersion relation and the transmission coefficient.","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128356793","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}
Pub Date : 2020-06-01DOI: 10.1109/ISCV49265.2020.9204257
Khalid Kandali, H. Bennis
In this paper, we propose a routing protocol using an adaptive K-Harmonic Means (RPKHM) in order to improve the lifetime of links between vehicles and to increase the stability of the vehicular network. First, the number and initial positions of the centroids are determined using a mathematical model that takes into account the total number of vehicles and the network topology. Whereas, the clustering is done using a similarity value based on the Euclidean distance, the difference in speed and direction of the vehicles. Finally, the maintenance of the clusters and the selection of new cluster heads are based on a cost function, which takes into account the total size of the free buffer and expected transmission count (ETX). The simulation results show the efficiency of the proposed scheme in terms of Packet Delivery Ratio, average End-to-End Delay, and Throughput.
{"title":"A Routing Scheme Using an Adaptive K-Harmonic Means Clustering for VANETs","authors":"Khalid Kandali, H. Bennis","doi":"10.1109/ISCV49265.2020.9204257","DOIUrl":"https://doi.org/10.1109/ISCV49265.2020.9204257","url":null,"abstract":"In this paper, we propose a routing protocol using an adaptive K-Harmonic Means (RPKHM) in order to improve the lifetime of links between vehicles and to increase the stability of the vehicular network. First, the number and initial positions of the centroids are determined using a mathematical model that takes into account the total number of vehicles and the network topology. Whereas, the clustering is done using a similarity value based on the Euclidean distance, the difference in speed and direction of the vehicles. Finally, the maintenance of the clusters and the selection of new cluster heads are based on a cost function, which takes into account the total size of the free buffer and expected transmission count (ETX). The simulation results show the efficiency of the proposed scheme in terms of Packet Delivery Ratio, average End-to-End Delay, and Throughput.","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130046106","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}
Pub Date : 2020-06-01DOI: 10.1109/ISCV49265.2020.9204065
Ayoub Berdeddouch, Ali Yahyaouy, Younés Benanni, R. Verde
Recommender Systems are software tools used to generate and provide suggestions for items and other entities to the users by exploiting various strategies. They are widely used and influence the daily life of almost everyone in different domains like e-commerce, social media, entertainment, or transportation in the mobility industry. The efficient generation of relevant recommendations in large-scale systems is a very complex task. This paper describes a deep recommender system for the most relevant K pick-up points for a driver. It is based on spatiotemporal features, points of interest (i.e POIs) and weather data using deep neural networks. Putting through a test with various features sets, we were able to achieve positive results. The effictiveness of our approach is demonstrated by the results, achieving a low loss value in most cases.
{"title":"Deep Based Recommender System For Relevant K Pick-up Points","authors":"Ayoub Berdeddouch, Ali Yahyaouy, Younés Benanni, R. Verde","doi":"10.1109/ISCV49265.2020.9204065","DOIUrl":"https://doi.org/10.1109/ISCV49265.2020.9204065","url":null,"abstract":"Recommender Systems are software tools used to generate and provide suggestions for items and other entities to the users by exploiting various strategies. They are widely used and influence the daily life of almost everyone in different domains like e-commerce, social media, entertainment, or transportation in the mobility industry. The efficient generation of relevant recommendations in large-scale systems is a very complex task. This paper describes a deep recommender system for the most relevant K pick-up points for a driver. It is based on spatiotemporal features, points of interest (i.e POIs) and weather data using deep neural networks. Putting through a test with various features sets, we were able to achieve positive results. The effictiveness of our approach is demonstrated by the results, achieving a low loss value in most cases.","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128913490","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}
Pub Date : 2020-06-01DOI: 10.1109/iscv49265.2020.9204209
{"title":"ISCV 2020 Cover Page","authors":"","doi":"10.1109/iscv49265.2020.9204209","DOIUrl":"https://doi.org/10.1109/iscv49265.2020.9204209","url":null,"abstract":"","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130205437","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}
Pub Date : 2020-06-01DOI: 10.1109/ISCV49265.2020.9204195
C. Khodris, B. Ahmed, C. Fouad, Abdellaoui Meriem, B. A. Idriss, H. Tairi
The emergence of artificial intelligence has influenced many aspects of our lives. Modern medicine relies heavily on diagnostic tools using image processing algorithms and artificial intelligence. Modern ophthalmology is not out of this context and has undergone a real revolution in recent years. Several studies have focused on combining artificial intelligence and image processing algorithms to provide powerful tools to assist ophthalmologists in their diagnoses and decisions. Recently, new devices combining these two sciences have been developed and the results seem promising. But where does the ophthalmologist stand in relation to this? In this article, we try to support the main scientific advances and describe the advantages, disadvantages and challenges.
{"title":"Artificial intelligence in ophthalmology: the ophthalmologist's opinion","authors":"C. Khodris, B. Ahmed, C. Fouad, Abdellaoui Meriem, B. A. Idriss, H. Tairi","doi":"10.1109/ISCV49265.2020.9204195","DOIUrl":"https://doi.org/10.1109/ISCV49265.2020.9204195","url":null,"abstract":"The emergence of artificial intelligence has influenced many aspects of our lives. Modern medicine relies heavily on diagnostic tools using image processing algorithms and artificial intelligence. Modern ophthalmology is not out of this context and has undergone a real revolution in recent years. Several studies have focused on combining artificial intelligence and image processing algorithms to provide powerful tools to assist ophthalmologists in their diagnoses and decisions. Recently, new devices combining these two sciences have been developed and the results seem promising. But where does the ophthalmologist stand in relation to this? In this article, we try to support the main scientific advances and describe the advantages, disadvantages and challenges.","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121307043","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}
Pub Date : 2020-06-01DOI: 10.1109/ISCV49265.2020.9204334
Elmo.J. Vasquez, Juan. C. Ortega
This research work aims to communicate the results of the design of a business continuity plan, in the department of technological innovation (DIT) for the Municipality of Cantón Suscal (MCS). We will analyze the IT area where the loss of business-critical data and the downtime of the systems are two of the greatest risks faced by those responsible for information technology. This research sought to develop the stages of a business continuity plan beginning with the knowledge of the entity, business impact analysis (BIA), risk identification, preventive measures and finally establishing recovery strategies that are the phases essential when we talk about business contingency. The research methodology was designed as an experimental descriptive exploratory study in which information is collected and an interaction occurs throughout the study in a short time. Finally, the MCS has a tool to minimize risks, through a design that marks the way to react to major incidents that may interrupt normal operation.
{"title":"Design of a business contingency plan. Case study: Municipality of Cantón Suscal.","authors":"Elmo.J. Vasquez, Juan. C. Ortega","doi":"10.1109/ISCV49265.2020.9204334","DOIUrl":"https://doi.org/10.1109/ISCV49265.2020.9204334","url":null,"abstract":"This research work aims to communicate the results of the design of a business continuity plan, in the department of technological innovation (DIT) for the Municipality of Cantón Suscal (MCS). We will analyze the IT area where the loss of business-critical data and the downtime of the systems are two of the greatest risks faced by those responsible for information technology. This research sought to develop the stages of a business continuity plan beginning with the knowledge of the entity, business impact analysis (BIA), risk identification, preventive measures and finally establishing recovery strategies that are the phases essential when we talk about business contingency. The research methodology was designed as an experimental descriptive exploratory study in which information is collected and an interaction occurs throughout the study in a short time. Finally, the MCS has a tool to minimize risks, through a design that marks the way to react to major incidents that may interrupt normal operation.","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133765877","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}
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