Afia Zafar1, Muhammad Aamir2, Nazri Mohd Nawi1, Ali Arshad3, Saman Riaz3, Abdulrahman Alruban4,*, Ashit Kumar Dutta5, Badr Almutairi6, Sultan Almotairi7,8
CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5641-5661, 2023, DOI:10.32604/cmc.2023.033733
Abstract In computer vision, convolutional neural networks have a wide range of uses. Images represent most of today’s data, so it’s important to know how to handle these large amounts of data efficiently. Convolutional neural networks have been shown to solve image processing problems effectively. However, when designing the network structure for a particular problem, you need to adjust the hyperparameters for higher accuracy. This technique is time consuming and requires a lot of work and domain knowledge. Designing a convolutional neural network architecture is a classic NP-hard optimization challenge. On the other hand, different datasets require different combinations of models… More >
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