Search Results - (( moral education based algorithm ) OR ( panel classification _ algorithm ))*

Lightning damage assessment on solar panels using in-house portable infrared thermography camera with Convolutional Neural Network (CNN) algorithm by Chandrasegaran, Ormiila, Mustapha, Faizal, Abdullah, Mohd Na’im, Anwar, Murniwati, Mustapha, Mazli, Adzis, Zuraimy

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Identifying Damage Types in Solar Panels Through Surface Image Analysis with Naive Bayes by Wiliani, Ninuk, T.K.A, Rahman, Ramli, Suzaimah

“…This work illustrates the potential of statistical feature extraction approaches for defect classification, while emphasizing the necessity for future improvements to boost the efficacy of feature extraction and classification techniques in practical applications.…”
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Humanizing Technology: The Role of Quranic Etiquettes and Shariah Ethics in AI-Based Learning Environments by Ayesha Siddika

“…The current study presents the emphasis of etiquettes mentioned in the Quran and Islamic principles to administrate AI-based education.…”

Defect Detection And Classification Of Silicon Solar Wafer Featuring Nir Imaging And Improved Niblack Segmentation by Mahdavipour, Zeinab

“…Meanwhile, a set of descriptors corresponding to Elliptic Fourier Features shape description is extracted for each defect and is evaluated for each cluster to use for clustering and classification part. The classification combines the analysis of defect intensity features, the application of unsupervised k-mean clustering and multi-class SVM algorithms. …”
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Development of electronic nose for classification of aromatic herbs using Artificial Intelligent techniques by Che Soh, Azura, Mohamad Radzi, Nur Fadzilah, Mohamad Yusof, Umi Kalsom, Ishak, Asnor Juraiza, Hassan, Mohd Khair

“…Two classification methods, Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) were used in order to investigate the performance of classification accuracy for this E-nose system. …”
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The classification of skateboarding trick manoeuvres: A K-nearest neighbour approach by Muhammad Ar Rahim, Ibrahim, Muhammad Amirul, Abdullah, Muhammad Nur Aiman, Shapiee, Mohd Azraai, Mohd Razman, Rabiu Muazu, Musa, Muhammad Aizzat, Zakaria, Noor Azuan, Abu Osman, Anwar P. P., Abdul Majeed

“…A variation of k-NN algorithms were tested based on the number of neighbours, as well as the weight and the type of distance metric used. …”
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