← Search

Renao Yan

3 accepted papers

2026

Turning Pre-Trained Vision Transformers into End-to-End Histopathology Whole Slide Image Models for Survival Prediction

CVPR 2026

Conventional whole slide image (WSI) analysis pipelines follow a two-stage process. First, an image encoder, such as a vision transformer (ViT), is used to perform batched offline feature extraction on a series of tiles cropped from the WSI. Second, a multiple instance learning (MIL) model is traine

Cited by 0SourcecodeScholar
2024

HIQ: One-Shot Network Quantization for Histopathological Image Classification

ICASSP 2024accepted

To deploy neural networks on clinical edge devices, quantization is the most commonly used method to compress the models, which requires a calibration set of hundreds of real images. However, due to privacy concerns, the scarcity of private histopathological images hinders the application of quantiz…

Cited by 0SourceScholar
2023

TexQ: Zero-shot Network Quantization with Texture Feature Distribution Calibration

NeurIPS 2023poster

Quantization is an effective way to compress neural networks. By reducing the bit width of the parameters, the processing efficiency of neural network models at edge devices can be notably improved. Most conventional quantization methods utilize real datasets to optimize quantization parameters and…