Finally, the sentiment classifier is constructed to learn the output distribution by applying the softmax function over the final representation. The experimental results on benchmark datasets prove ...

Binunya, F. and Zhou, H. (2025) Multilingual Text Recognition and Assistance for Low-Resource Languages Using Computer Vision. Open Access Library Journal, 12, 1-20. doi: 10.4236/oalib.1113574 .

We propose a novel graph neural network (GNN) structure that jointly optimize beamforming vectors and user association while guaranteeing association output as integers. The integer association ...

The Softmax output provides the probabilities associated with normal or osteoporosis conditions. The model is compiled using the Adam optimizer with a learning rate of 0.0002, employing categorical ...

The edge representations are linked to the ground-truth tour through a softmax output layer, which allows us to train the model parameters end-to-end by minimizing the cross-entropy loss via gradient ...

In this paper, we propose a self-organized graph neural network (SOGNN) for cross-subject EEG emotion recognition. Unlike the previous studies based on pre-constructed and fixed graph structure, the ...