Search Results - (( (emotion OR motion) detection system algorithm ) OR ( data classification based algorithm ))

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  1. 1

    Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool by Nurshafiqa Saffah, Mohd Sharif

    Published 2018
    “…Each respondent underwent two mathematical game sessions using a smartphone with a two-minute break in between each session. From the data analysis using WEKA software, the production rules classifier (PART) is found to be the most accurate classification algorithm in classifying the emotion which yields the highest precision percentage of 99.6% compared to J48 (99.5%) and Naïve Bayes (96.2%). …”
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    Thesis
  2. 2

    Neural network classifier for hand motion detection from EMG signal by Ibrahimy, Muhammad Ibn, Khalifa, Othman Omran

    Published 2011
    “…A backpropagation (BP) network with Levenberg-Marquardt training algorithm has been utilized for the classification of EMG signals. …”
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    Book Chapter
  3. 3

    Detection and Classification of Moving Objects for an Automated Surveillance System by Md. Tomari, Mohd Razali

    Published 2006
    “…A completely automated system means a computer will perform the entire task from low level detection to higher level motion analysis. …”
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    Thesis
  4. 4

    Detection and classification of moving objects for an automated surveillance system by Md Tomari, Mohd Razali

    Published 2006
    “…A completely automated system means a computer will perforin the entire task from low level detection to higher level motion analysis. …”
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    Thesis
  5. 5

    Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant by Morshidi, Malik Arman

    Published 2007
    “…In this research, a vision system algorithm has been developed to identify and locate base of young corn trees based upon robot vision technology, pattern recognition techniques, and knowledge-based decision theory. …”
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    Thesis
  6. 6

    Eye fixation versus pupil diameter as eye- tracking features for virtual reality emotion classification by Lim Jia Zheng, James Mountstephens, Jason Teo

    Published 2022
    “…Therefore, this empirical study has shown that eyetracking- based emotion recognition systems would benefit from using features based on eye fixation data rather than pupil size.…”
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    Proceedings
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    Detection and classification of moving objects for an automated surveillance system by Md Tomari, Mohd Razali

    Published 2006
    “…A completely automated system means a computer will perforin the entire task from low level detection to higher level motion analysis. …”
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    Thesis
  10. 10

    A review: radar-based fall detection sensor / Hidayatusherlina Razali ... [et al.] by Razali, Hidayatusherlina, Abd. Rashid, Nur Emileen, Nasarudin, Muhammad Nazrin Farhan, Ismail, Nor Najwa, Ismail Khan, Zuhani, Enche Ab Rahim, Siti Amalina

    Published 2024
    “…Fall recognition involves steps: sensor type, data pre-processing, and data classification. This study examines radar's use in fall detection and how fall detection systems can enhance people's lives.…”
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    Article
  11. 11

    Vader lexicon and support vector machine algorithm to detect customer sentiment orientation by Vivine Nurcahyawati, ., Zuriani, Mustaffa

    Published 2023
    “…Additionally, the study showcases the novelty and superiority of the annotation process used for detecting customer orientation classifications. Methods: This study employs a method to compare the classification performance of the Vader lexicon annotation process with manual annotation. …”
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    Article
  12. 12

    Forward scattering radar for real-time detection of human activities and fall classification by Abdulhameed, Ali Ahmed

    Published 2019
    “…The experimental results revealed that the FSR system has the ability to detect and differentiate the low-speed human body motions when performing daily activities and fall events. …”
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    Thesis
  13. 13

    A review of chewing detection for automated dietary monitoring by Minhad, Khairun Nisa’, Selamat, Nur Asmiza, Yanxin, Wei, Md Ali, Sawal Hamid, Sobhan Bhuiyan, Mohammad Arif, Kelvin Jian, Aun Ooi, Samdin, Siti Balqis

    Published 2022
    “…The decision tree approach was more robust and its classification accuracy (75%–93.3%) was higher than those of the Viterbi algorithm-based finite-state grammar approach, which yielded 26%–97% classification accuracy. …”
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    Article
  14. 14

    WEBCAM MOTION DETECTION USINGVISUAL BASIC by Abdullah, Ilyana

    Published 2005
    “…Watch Eyes Motion Detection System is aproject used to enhance student's interest in multimedia system development, but at the same time the project can be used as motion detection system that will help any person in doing research in motion detection purposes. …”
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    Final Year Project
  15. 15

    Web Camera Application For Motion Detection by Koay, Su Yeong

    Published 2003
    “…The new method to detect motion is "vision motion detection". It is the artificial way of machine vision system compared to human's vision in detecting motion. …”
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    Thesis
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    Vehicle Monitoring System Using Motion Detection Algorithms For USM Campus. by Osman, Mohd. Azam, Talib, Abdullah Zawawi, Tan, Kian Lam, Wong, Poh Lee, Sabudin, Maziani

    Published 2007
    “…With the possible introduction of the motion detection and character recognition algorithms in security systems of the future, vehicle identities such as license plate numbers can be captured and processed at the security post to make it possible for the vehicles to be monitored remotely. …”
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    Conference or Workshop Item
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    Human Spontaneous Emotion Detection System by Radin Monawir, Radin Puteri Hazimah

    Published 2018
    “…Having smart computerized system which can understand and instantly gives appropriate response to human is the utmost motive in human and computer interaction (HCI) field.It is argued either HCI is considered advance if human could not have natural and comfortable interaction like human to human interaction.Besides,despite of several studies regarding emotion detection system, current system mostly tested in laboratory environment and using mimic emotion.Realizing the current system research lack of real life or genuine emotion input,this research work comes up with the idea of developing a system that able to recognize human emotion through facial expression.Therefore,the aims of this study are threefold which are to enhance the algorithm to detect spontaneous emotion,to develop spontaneous facial expression database and to verify the algorithm performance.This project used Matlab programming language,specifically Viola Jones method for features tracking and extraction,then pattern matching for emotion classification purpose.Mouth feature is used as main features to identify the emotion of the expression.For verification purpose,the mimic and spontaneous database which are obtained from internet,open source database or novel (own) developed databases are used.Basically,the performance of the system is indicated by emotion detection rate and average execution time.At the end of this study,it is found that this system is suitable for recognizing spontaneous facial expression (63.28%) compared to posed facial expression (51.46%).The verification even better for positive emotion with 71.02% detection rate compared to 48.09% for negative emotion detection rate.Finally,overall detection rate of 61.20% is considered good since this system can execute result within 3s and use spontaneous input data which known as highly susceptible to noise.…”
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    Thesis