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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

“…Statistical criteria, including recall, specificity, and area under the curve (AUC), are employed to assess model performance. The findings indicate that the GNB algorithm surpasses BNB, with a mean average precision (mAP) of 39.83% with an 85:15 training-test ratio, whereas BNB reaches a maximum mAP of 29.25% at a 90:10 ratio. …”
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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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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

“…It was shown from the present preliminary investigation, that the k-NN model which employs k = 1 with an equal weight applied to the Euclidean distance metric yielded a classification accuracy of 85%. …”
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