11 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…
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…
Regional Style and Color Transfer
Zhicheng Ding, Panfeng Li, Qikai Yang +2
This paper presents a novel contribution to the field of regional style transfer. Existing methods often suffer from the drawback of applying style homogeneously across the entire…
Confidence Trigger Detection: Accelerating Real-time Tracking-by-detection Systems
Zhicheng Ding, Zhixin Lai, Siyang Li +3
Real-time object tracking necessitates a delicate balance between speed and accuracy, a challenge exacerbated by the computational demands of deep learning methods. In this paper,…
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…