Search Results - (( facial expression method algorithm ) OR ( java application optimization algorithm ))

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  1. 1

    Deep learning methods for facial expression recognition by Mohammad Masum Refat, Chowdhury, Zainul Azlan, Norsinnira

    Published 2019
    “…Deep learning is very popular methods for facial expression recognition (FER) and classification. …”
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    Proceeding Paper
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    Facial expression type recognition using K-Nearest Neighbor algorithm / Norhafizah Saffian by Saffian, Norhafizah

    Published 2017
    “…Based on this calculation, the accuracy of this algorithm is 93% using the k values of 5. The future work that continue based on this project proposed is by study and applied other type of algorithm that can produce the high performance and accuracy of classification of facial feature for facial expression recognition.…”
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    Thesis
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    3D face registration across pose variation and facial expression using cross profile alignment by Anuar, Laili Hayati

    Published 2011
    “…The experiments are usually conducted using cleaned and frontalviewed face models, neglecting the facial variation that often occur in real-time scenarios, such as pose variation, facial expression, facial outliers and occlusion. …”
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    Thesis
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    Static Facial Expression Recognition in the wild: Taxonomy, trends and challenges by Jing-Zhi Koay, Jason Teo

    Published 2025
    “…In recent years, Facial Expression Recognition (FER) has gained significant at-tention due to its wide application and potential in various domains. …”
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    Article
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    A new approach in solving illumination and facial expression problems for face recognition by Yee, Wan Wong, Kah, Phooi Seng, Li, Minn Ang

    Published 2009
    “…In this paper, a novel dual optimal multiband features (DOMF) method is presented to increase the robustness of face recognition system to illumination and facial expression variations.The wavelet packet transform first decomposes image into low-, mid- and high-frequency subbands and the multiband feature fusion technique is incorporated to select the subbands that are invariant to illumination and expression variation separately.These subbands form the optimal feature sets.Parallel radial basis function neural networks are employed to classify these feature sets.The scores generated by the neural networks are combined by an adaptive fusion mechanism where the level of illumination variations of the testing image is estimated and the weights are assigned to the scores accordingly.The experimental results show that DOMF outperforms other algorithms and also achieves promising performance on illumination and facial expression variation conditions.…”
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    Conference or Workshop Item
  8. 8

    A new descriptor for smile classification based on cascade classifier in unconstrained scenarios by Hassen, Oday Ali, Abu, Nur Azman, Zainal Abidin, Zaheera, Saad, Mohamed Darwish

    Published 2021
    “…In the development of human–machine interfaces, facial expression analysis has attracted considerable attention, as it provides a natural and efficient way of communication. …”
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    Article
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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
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    Facial age range estimation using geometric ratios and hessian-based filter wrinkle analysis by Razalli, Husniza

    Published 2016
    “…In this thesis, a new automatic facial age range estimation method using geometric ratios and wrinkle analysis is proposed. …”
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    Thesis
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    Classification of transient facial wrinkle by Rosdiyana, Samad, Mohammad Zarif, Rosli, Nor Rul Hasma, Abdullah, Mahfuzah, Mustafa, Dwi, Pebrianti, Nurul Hazlina, Noordin

    Published 2019
    “…Classification of transient wrinkle is an important application in research related to the skin aging, facial expression and skin analysis. Many researches have been done in the detection or classification of wrinkle, but it still needs some improvement in the algorithms, either in feature extraction part or classification. …”
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    Conference or Workshop Item
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    Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

    Published 2016
    “…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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    Conference or Workshop Item
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    Face expression recognition using artificial neural network (ANN) / Mazuraini Ghani by Ghani, Mazuraini

    Published 2005
    “…This project is all about implementing the back-propagation neural network algorithm in classification of face expression. This project has 3 objectives. …”
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    Thesis
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    Route Optimization System by Zulkifli, Abdul Hayy

    Published 2005
    “…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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    Final Year Project