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Found 6 papers, 0 papers with code
Transformer-Based Classification Outcome Prediction for Multimodal Stroke Treatment
This study proposes a multi-modal fusion framework Multitrans based on the Transformer architecture and self-attention mechanism.
Utilizing the LightGBM Algorithm for Operator User Credit Assessment Research
First, for the massive data related to user evaluation provided by operators, key features are extracted by data preprocessing and feature engineering methods, and a multi-dimensional feature set with statistical significance is constructed; then, linear regression, decision tree, LightGBM, and other machine learning algorithms build multiple basic models to find the best basic model; finally, integrates Averaging, Voting, Blending, Stacking and other integrated algorithms to refine multiple fusion models, and finally establish the most suitable fusion model for operator user evaluation.
Fostc3net:A Lightweight YOLOv5 Based On the Network Structure Optimization
In addition, a FasterNet module is introduced to replace the c3 module in the YOLOv5 Backbone.
A Multimodal Fusion Network For Student Emotion Recognition Based on Transformer and Tensor Product
This paper introduces a new multi-modal model based on the Transformer architecture and tensor product fusion strategy, combining BERT's text vectors and ViT's image vectors to classify students' psychological conditions, with an accuracy of 93. 65%.
Improved YOLOv5 Based on Attention Mechanism and FasterNet for Foreign Object Detection on Railway and Airway tracks
In recent years, there have been frequent incidents of foreign objects intruding into railway and Airport runways.
Financial Time-Series Forecasting: Towards Synergizing Performance And Interpretability Within a Hybrid Machine Learning Approach
In the realm of cryptocurrency, the prediction of Bitcoin prices has garnered substantial attention due to its potential impact on financial markets and investment strategies.
