Search Results - (( based interactive learning algorithm ) OR ( using classification based algorithm ))

Autism Spectrum Disorder Classification Using Deep Learning by Abdulrazak Yahya, Saleh, Lim Huey, Chern

“…The goal of this paper is to evaluate the deep learning algorithm for people placed in the Autism Spectrum Disorder (ASD) classification. …”
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Gender classification based on asian faces using deep learning by Janahiraman T.V., Subramaniam P.

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

“…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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Applying SAX-based time series analysis to classify EEG signal using a COTS EEG device by Shanmuga, Pillai A/L Murutha Muthu

“…This research will investigate the application of the Symbolic Aggregate Approximation (SAX) algorithm on top of known supervised machine learning techniques to perform EEG signal classification. …”
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Genetic ensemble biased ARTMAP method of ECG-Based emotion classification by Loo, C.K., Liew, W.S., Sayeed, M.S.

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Compact Convolutional neural network (CNN) based on SincNet for end-to-end motor imagery decoding and analysis by Ahmad Izzuddin, Tarmizi, Mat Safri, Norlaili, Othman, Mohd Afzan

“…In order to validate the performance of proposed algorithms, two datasets were used; the first is the publicly available BCI Competition IV dataset 2a, which was often used as a benchmark in validating motor imagery classification algorithms, and the second is a dataset consists of primary data initially collected to study the difference between motor imagery and mental-task associated motor imagery BCI and was used to test the plausibility of the proposed algorithm in highlighting the differences in terms of cortical rhythms. …”
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An Empirical Evaluation of Artificial Intelligence Algorithm for Hand Posture Classification by Hussain, A., Hussain, S.S., Uddin, M.M., Zubair, M., Kumar, P., Umair, M.

“…In this study, exhaustive empirical research of the machine learning algorithm for hand posture classification has been established. …”
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A COMPARATIVE STUDY OF MACHINE LEARNING MODELS FOR PREDICTION OF AUTISM SPECTRUM DISORDER USING SCREENING DATA by Yeap, Ming Yue

“…This project aims to predict ASD traits in adults based on screening data using a machine learning approach. …”
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Simulation on Emotion Recognition for Autism Therapy by Adzmi, Muhammad Azrin

“…The program will be used by the therapist during therapy session with the autism child in order to create more exciting environment for them to learn about the classification of basic human emotions with the help of human-computer interaction. …”
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FIS-PNN: a hybrid computational method for protein-protein interactions prediction using the secondary structure information by Sakhinah Abu Bakar, Javid Taheri, Albert Y Zomaya

“…As a result, they must interact with each other. In this study we used our approach, namely FIS-PNN, to predict the interacting proteins in yeast from the information of their secondary structures using hybrid machine learning algorithms. …”
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Spiking Neural Network For Energy Efficient Learning And Recognition by Wong, Yan Chiew, Wang, Ning Lo

“…The use of applications consumes energy and hard to perform through standard programmed algorithms. …”
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Developing framework for natphoric computer-aided web-based kansei engineering / Mohammad Bakri Che Haron by Che Haron, Mohammad Bakri

“…The Natphoric algorithm learns the process done by training with sets of training data from previous KE research works. …”
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Predictive analytics for the sentiment of malaysian place of interest using machine learning models by Qiryn Adriana, Kharul Zaman

“…The focus of this study is to conduct Natural Language Processing (NLP) on tweets and make a better classification of sentiment using Malaya. Furthermore, this study also trains three machine learning algorithms to predict the sentiment of textual data. …”
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Identifying the correct articulation point of a Quranic letters of the throat (al-halqu) makhraj by Othman, Ahmad Al Baqir, Ahmad, Salmiah, Badron, Khairayu, Altalmas, Tareq M. K.

“…Data was trained using an improved deep learning Convolutional Neural Network (CNN) classification model. …”
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Filter-Wrapper Methods For Gene Selection In Cancer Classification by Alomari, Osama Ahmad Suleiman

“…This study proposes new hybrid filter-wrapper methods based on Maximum Relevancy Minimum Redundancy (MRMR) as a filter approach and adapted bat-inspired algorithm (BA) as a wrapper approach. …”
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Exploring classification for sentiment analysis from halal based tweets by Setik, Roziyani, Raja Lope Ahmad, Raja Mohd Tariqi, Marjudi, Suziyanti

“…It usually assigns a polarity of “positive”, “negative” or “neutral”. It uses an algorithmic technique to capture people's thoughts, sentiments, and emotions by incorporating Natural Language Processing and Machine Learning technology. …”
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Design and performance analysis of artificial neural network for hand motion detection from EMG signals by Ibrahimy, Muhammad Ibn, Ahsan, Md. Rezwanul, Khalifa, Othman Omran

“…The conventional and most effective time and timefrequency based features are extracted and normalized. The neural network has been trained with the normalized feature set with supervised learning method. …”
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Improving multi-resident activity recognition in smart home using multi label classification with adaptive profiling by Mohamed, Raihani

“…Furthermore, there is tendency that multi label classifications used instead of traditional single label classification technique. …”
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Enhanced emotion recognition in videos: a convolutional neural network strategy for human facial expression detection and classification by Ashraf, Arselan, Gunawan, Teddy Surya, Arifin, Fatchul, Kartiwi, Mira, Sophian, Ali, Habaebi, Mohamed Hadi

“…Despite extensive research employing machine learning algorithms like convolutional neural networks (CNN), challenges remain concerning input data processing, emotion classification scope, data size, optimal CNN configurations, and performance evaluation. …”
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CNN-LSTM: hybrid deep neural network for network intrusion detection system; a case by Halbouni, Asmaa Hani, Gunawan, Teddy Surya, Habaebi, Mohamed Hadi, Halbouni, Murad, Kartiwi, Mira, Ahmad, Robiah

“…Numerous studies implemented machine learning algorithms to develop an effective IDS; however, with the advent of deep learning algorithms and artificial neural networks that can generate features automatically without human intervention, researchers began to rely on deep learning. …”
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