6 papers
Data Augmentation Through Random Style Replacement
Qikai Yang, Cheng Ji, Huaiying Luo +2
In this paper, we introduce a novel data augmentation technique that combines the advantages of style augmentation and random erasing by selectively replacing image subregions with…
Harnessing Earnings Reports for Stock Predictions: A QLoRA-Enhanced LLM Approach
Haowei Ni, Shuchen Meng, Xupeng Chen +7
Accurate stock market predictions following earnings reports are crucial for investors. Traditional methods, particularly classical machine learning models, struggle with these pre…
Evaluating Modern Approaches in 3D Scene Reconstruction: NeRF vs Gaussian-Based Methods
Yiming Zhou, Zixuan Zeng, Andi Chen +7
Exploring the capabilities of Neural Radiance Fields (NeRF) and Gaussian-based methods in the context of 3D scene reconstruction, this study contrasts these modern approaches with…
A Review of Electromagnetic Elimination Methods for low-field portable MRI scanner
Wanyu Bian, Panfeng Li, Mengyao Zheng +5
This paper analyzes conventional and deep learning methods for eliminating electromagnetic interference (EMI) in MRI systems. We compare traditional analytical and adaptive techniq…
Time Series Modeling for Heart Rate Prediction: From ARIMA to Transformers
Haowei Ni, Shuchen Meng, Xieming Geng +5
Cardiovascular disease (CVD) is a leading cause of death globally, necessitating precise forecasting models for monitoring vital signs like heart rate, blood pressure, and ECG. Tra…
Enhance Image-to-Image Generation with LLaVA-generated Prompts
Zhicheng Ding, Panfeng Li, Qikai Yang +1
This paper presents a novel approach to enhance image-to-image generation by leveraging the multimodal capabilities of the Large Language and Vision Assistant (LLaVA). We propose a…