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Titlebook: Intelligent Manufacturing and Mechatronics; Proceedings of the 2 Zamberi Jamaludin,Mohd Najib Ali Mokhtar Conference proceedings 2020 Sprin

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Weng Sun Tong,Tsung Heng Chiew,Zamberi Jamaludin,Ahmad Yusairi Bani Hashim,Lokman Abdullah,Nur Aidaw
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Normaisharah Mamat,Fitri Yakub,Sheikh Ahmad Zaki Shaikh Salim,Mohd Zamzuri Ab Rashid,Sharifah Munawa
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Predicting Outcomes in Patients with Traumatic Brain Injury Using Machine Learning Modelsthms to learn patterns by studying data directly without being explicitly programmed. This paper compares the different ways in which predictive models evaluate the potential of ML for TBI outcome prediction. A literature survey of latest articles from 2016 to 2018 reveals that the predictions of ex
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Blood Vessel Detection Monitoring System and Mobile Notification for Diabetic Retinopathy Diagnosism Digital Retina Images for Vessel Extraction (DRIVE) dataset. The resulting images are compared with the benchmark images based on a few image quality assessment (IQA) such as accuracy, sensitivity and specificity. The total average of accuracy is 92.64%, while sensitivity and specificity obtained
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Reduction of Salt-and-Pepper Noise from Digital Grayscale Image by Using Recursive Switching Adaptive restoration stages. In the noise detection stage, salt-and-pepper pixel candidates are identified. Then, in the restoration stage, an adaptive method is used for the restoration. The size of the filter is expanding until there are at least eight noise-free pixel candidates defined by the window. A
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