{"title":"Human – Ear Recognition Using Scale Invariant Feature Transform","authors":"Abbas H. Hassin, D. Abbood","doi":"10.52098/airdj.20217","DOIUrl":"https://doi.org/10.52098/airdj.20217","url":null,"abstract":"Biometrics techniques are the standard of a wide group of many applications for a human’s identification and verification issues. Because of this reason, a high scale of security needs to search for a new way to identify the person arises. In this paper, establish a human ear recognition system is proposed. This system combines four main phases: ear detection, ear feature extraction, ear recognition, and confirmation. The essential of the proposed system is to divide the ear image into the skin and non-skin pixels using a likelihood skin detector. The likelihood image processes by morphological operations to complete ear regions. Scale-invariant feature transform uses for extracting the fixed features of the ear. Ear recognition includes two modes identification mode and verification mode. Euclidean Distance Measure (EDM) uses for similarity measure between the first image in the database and a new image. According to the three experiments conducted in this paper, the results of the different datasets, the accuracy ratio are 100%, 92%.and 92% respectively.","PeriodicalId":166900,"journal":{"name":"Artificial Intelligence & Robotics Development Journal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115852099","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}
{"title":"Viability of Robots in Improving Autistic Student’s Engagement and Happiness When Learning","authors":"M. Yousif","doi":"10.52098/AIRDJ.202114","DOIUrl":"https://doi.org/10.52098/AIRDJ.202114","url":null,"abstract":"The adoption of robotics in other industries is increasing exponentially at a rapid pace due to increased interest in the field. Advancements in robotic technology allow them to be more capable in teaching a variety of topics while costing much less than even just a decade ago. This means that robots are more ready than ever before to be deployed globally in the educational space. The aim of paper is to check the viability of robots in improving autistic students’ engagement and happiness, rather than just their performance. 6 autistic students aged 7 – 12 took part in this experiment (4 male and 2 female). Several different structured scenarios and tasks were used to evaluate the student’s happiness and engagement on a scale of five. It was found that the children showed an improvement of 144% across the board, when comparing the happiness score and an increase of 61.4% for the students’ engagement score. It was also found that the children were showing much more emotion and were much more responsive during the tasks.","PeriodicalId":166900,"journal":{"name":"Artificial Intelligence & Robotics Development Journal","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128101963","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}