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  • Open Access

    ARTICLE

    Eye-Tracking Based Autism Spectrum Disorder Diagnosis Using Chaotic Butterfly Optimization with Deep Learning Model

    Tamilvizhi Thanarajan1, Youseef Alotaibi2, Surendran Rajendran3,*, Krishnaraj Nagappan4

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1995-2013, 2023, DOI:10.32604/cmc.2023.039644 - 30 August 2023

    Abstract Autism spectrum disorder (ASD) can be defined as a neurodevelopmental condition or illness that can disturb kids who have heterogeneous characteristics, like changes in behavior, social disabilities, and difficulty communicating with others. Eye tracking (ET) has become a useful method to detect ASD. One vital aspect of moral erudition is the aptitude to have common visual attention. The eye-tracking approach offers valuable data regarding the visual behavior of children for accurate and early detection. Eye-tracking data can offer insightful information about the behavior and thought processes of people with ASD, but it is important to… More >

  • Open Access

    ARTICLE

    Robust and High Accuracy Algorithm for Detection of Pupil Images

    Waleed El Nahal1, Hatim G. Zaini2, Raghad H. Zaini3, Sherif S. M. Ghoneim4,*, Ashraf Mohamed Ali Hassan5

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 33-50, 2022, DOI:10.32604/cmc.2022.028190 - 18 May 2022

    Abstract Recently, many researchers have tried to develop a robust, fast, and accurate algorithm. This algorithm is for eye-tracking and detecting pupil position in many applications such as head-mounted eye tracking, gaze-based human-computer interaction, medical applications (such as deaf and diabetes patients), and attention analysis. Many real-world conditions challenge the eye appearance, such as illumination, reflections, and occasions. On the other hand, individual differences in eye physiology and other sources of noise, such as contact lenses or make-up. The present work introduces a robust pupil detection algorithm with and higher accuracy than the previous attempts for… More >

  • Open Access

    RETRACTION

    Retraction Notice to: Implementation System of Human Eye Tracking Algorithm Based on FPGA

    Zhong Liu1, 2, Xin’an Wang1, Chengjun Sun1, Ken Lu3

    CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1487-1487, 2020, DOI:10.32604/cmc.2020.04597

    Abstract This article has no abstract. More >

  • Open Access

    RETRACTION

    RETRACTED: Implementation System of Human Eye Tracking Algorithm Based on FPGA

    Zhong Liu1,2, Xin’an Wang1, Chengjun Sun1, Ken Lu3

    CMC-Computers, Materials & Continua, Vol.58, No.3, pp. 653-664, 2019, DOI:10.32604/cmc.2019.04597

    Abstract With the high-speed development of transportation industry, highway traffic safety has become a considerable problem. Meanwhile, with the development of embedded system and hardware chip, in recent years, human eye detection eye tracking and positioning technology have been more and more widely used in man-machine interaction, security access control and visual detection.
    In this paper, the high parallelism of FPGA was utilized to realize an elliptical approximate real-time human eye tracking system, which was achieved by the series register structure and random sample consensus (RANSAC), thus improving the speed of image processing without using external memory. Because… More >

  • Open Access

    ARTICLE

    Statistical Analysis and Multimodal Classification on Noisy Eye Tracker and Application Log Data of Children with Autism and ADHD

    Mahiye Uluyagmur Ozturka, Ayse Rodopman Armanb, Gresa Carkaxhiu Bulutc, Onur Tugce Poyraz Findikb, Sultan Seval Yilmazd, Herdem Aslan Gencb, M. Yanki Yazgane,f, Umut Tekera, Zehra Cataltepea

    Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 891-905, 2018, DOI:10.31209/2018.100000058

    Abstract Emotion recognition behavior and performance may vary between people with major neurodevelopmental disorders such as Autism Spectrum Disorder (ASD), Attention Deficit Hyperactivity Disorder (ADHD) and control groups. It is crucial to identify these differences for early diagnosis and individual treatment purposes. This study represents a methodology by using statistical data analysis and machine learning to provide help to psychiatrists and therapists on the diagnosis and individualized treatment of participants with ASD and ADHD. In this paper we propose an emotion recognition experiment environment and collect eye tracker fixation data together with the application log data More >

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