This method improves classification accuracy and enhances model robustness. Experimental results show that the proposed method outperforms conventional ViT and CNN fine-tuning methods. It achieves a ...

For classification tasks, Binary Cross-Entropy is suitable ... to minimize the loss. In Python, libraries like TensorFlow and PyTorch offer built-in loss functions which can be easily integrated ...

However, we are unsure about one aspect: when using 'cross_entropy' as the loss function, is there an automatic adjustment within the model considering that binary cross entropy typically expects the ...

Since the large numbers in exp() function of python returns 'inf' (more than 709 in python 2.7.11), so in these version of cross entropy loss without 'softmax_cross_entropy_with_logits()' function, I ...

To circumvent these two issues, we propose in this paper a binary cross-entropy (BCE) type of loss function and present a method to train the deep neural network (DNN) models based on the proposed ...

Firstly, we utilize a network model architecture combining Gelu activation function and deep neural network; Secondly, the cross-entropy ... in python to check whether there are missing values in each ...