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Noor Farisya Mohd

As seen in: Nature, MDPI
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Articles

Hybrid Aquila optimizer–Harris Hawks optimization for CNN hyperparameter tuning in brain tumor classification

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By Manoj Kumar, Noor Farisya Mohd, Ankur Goyal, Deepak Parashar, Rijwan Khan, G. Shivam
| Nature Verified
Abstract Magnetic resonance imaging (MRI) is hard to categorize properly in terms of interclass similarity, there is data imbalance, and sensitive clinical decision-making: but the performance of convolutional neural networks (CNNs) highly relies on effective, yet computationally costly, hyperparameter tuning.
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Assessing Impact of Cooking Methods on the Physicochemical and Sensory Properties of Instant Fortified Rice Congee for the Elderly

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By Anida Yusoff, Eng-Keng Seow, Noor Farisya Mohd, Siti Roha Ab
| MDPI
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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