Hajira Saleem1, Faisal Riaz1, Asadullah Shaikh2, Khairan Rajab2,3, Adel Rajab2,*, Muhammad Akram2, Mana Saleh Al Reshan2
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2285-2302, 2022, DOI:10.32604/cmc.2022.022726
Abstract Deep learning techniques, particularly convolutional neural networks (CNNs), have exhibited remarkable performance in solving vision-related problems, especially in unpredictable, dynamic, and challenging environments. In autonomous vehicles, imitation-learning-based steering angle prediction is viable due to the visual imagery comprehension of CNNs. In this regard, globally, researchers are currently focusing on the architectural design and optimization of the hyperparameters of CNNs to achieve the best results. Literature has proven the superiority of metaheuristic algorithms over the manual-tuning of CNNs. However, to the best of our knowledge, these techniques are yet to be applied to address the problem of imitation-learning-based steering angle prediction.… More >
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