Keywords: pain intensity classification, multiscale convolutional networks, transformer encoder, squeeze-and-excitation residual network, deep learning, EDA, temporal convolutional network, BioVid ...

This article explores some of the most influential deep learning architectures: Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Generative Adversarial Networks (GANs), ...

Use of BERT (Bidirectional Encoder Representations from Transformers)-Based Deep Learning Method for Extracting Evidences in Chinese Radiology Reports: Development of a Computer-Aided Liver Cancer ...

This repository implements deep learning transformer models in MATLAB. [sentiment, scores] = finbert.sentimentModel(X,parameters) also returns the corresponding sentiment scores in the range [-1 1].

The transformer encoder serves as a graph learner, extracting attention relationships between nodes and edges in the graph representation. Concurrently, a deep reinforcement learning agent is ...

This study proposes Transformer- Kan,a novel deep learning model for short-term wind power forecasting that synergistically integrates the Transformer architecture with the Kolmogorov-Arnold Network ...

Current methods, \eg self-report scales, can be biased and inconsistent. Therefore, there is a need for objective and automatic pain intensity evaluation. In this paper, we propose PainAttnNet, a ...