[Retracted] Classification and Detection of Autism Spectrum Disorder Based on Deep Learning Algorithms

Table 2

Experimental setup.

Hardware	Software/libraries
Processor core I7	TensorFlow library; Keras library; Panda seaborn; Matplotlib; Numpy
8 GB RAM

Note. The model parameters were set with 100 epochs and with a batch size of 32. To avoid overfitting and to optimize the training time, the early stop strategy was used, whereby the training was stopped after 28 epochs. The parameters of the deep learning model are shown in Table 3.