5 citations · 22 across the 15 of their papers we have counts for
15 papers
Information-Theoretic Generalization Bounds of Replay-based Continual Learning
Wen Wen, Tieliang Gong, Zeyu Gao +3
Continual learning (CL) has emerged as a dominant paradigm for acquiring knowledge from sequential tasks while avoiding catastrophic forgetting. Although many CL methods have been…
Spiking Neural Network for Ultra-low-latency and High-accurate Object Detection
Jinye Qu, Zeyu Gao, Tielin Zhang +3
Spiking Neural Networks (SNNs) have garnered widespread interest for their energy efficiency and brain-inspired event-driven properties. While recent methods like Spiking-YOLO have…
Enhance Sample Efficiency and Robustness of End-to-end Urban Autonomous Driving via Semantic Masked World Model
Zeyu Gao, Yao Mu, Chen Chen +4
End-to-end autonomous driving provides a feasible way to automatically maximize overall driving system performance by directly mapping the raw pixels from a front-facing camera to…
Meta Mask Correction for Nuclei Segmentation in Histopathological Image
Jiangbo Shi, Chang Jia, Zeyu Gao +3
Nuclei segmentation is a fundamental task in digital pathology analysis and can be automated by deep learning-based methods. However, the development of such an automated method re…
PIMIP: An Open Source Platform for Pathology Information Management and Integration
Jialun Wu, Anyu Mao, Xinrui Bao +5
Digital pathology plays a crucial role in the development of artificial intelligence in the medical field. The digital pathology platform can make the pathological resources digita…
BioIE: Biomedical Information Extraction with Multi-head Attention Enhanced Graph Convolutional Network
Jialun Wu, Yang Liu, Zeyu Gao +3
Constructing large-scaled medical knowledge graphs can significantly boost healthcare applications for medical surveillance, bring much attention from recent research. An essential…
A Personalized Diagnostic Generation Framework Based on Multi-source Heterogeneous Data
Jialun Wu, Zeyu Gao, Haichuan Zhang +4
Personalized diagnoses have not been possible due to sear amount of data pathologists have to bear during the day-to-day routine. This lead to the current generalized standards tha…
W-Net: A Two-Stage Convolutional Network for Nucleus Detection in Histopathology Image
Anyu Mao, Jialun Wu, Xinrui Bao +3
Pathological diagnosis is the gold standard for cancer diagnosis, but it is labor-intensive, in which tasks such as cell detection, classification, and counting are particularly pr…
A Precision Diagnostic Framework of Renal Cell Carcinoma on Whole-Slide Images using Deep Learning
Jialun Wu, Haichuan Zhang, Zeyu Gao +4
Diagnostic pathology, which is the basis and gold standard of cancer diagnosis, provides essential information on the prognosis of the disease and vital evidence for clinical treat…
Instance-based Vision Transformer for Subtyping of Papillary Renal Cell Carcinoma in Histopathological Image
Zeyu Gao, Bangyang Hong, Xianli Zhang +6
Histological subtype of papillary (p) renal cell carcinoma (RCC), type 1 vs. type 2, is an essential prognostic factor. The two subtypes of pRCC have a similar pattern, i.e., the p…
Nuclei Grading of Clear Cell Renal Cell Carcinoma in Histopathological Image by Composite High-Resolution Network
Zeyu Gao, Jiangbo Shi, Xianli Zhang +6
The grade of clear cell renal cell carcinoma (ccRCC) is a critical prognostic factor, making ccRCC nuclei grading a crucial task in RCC pathology analysis. Computer-aided nuclei gr…
Renal Cell Carcinoma Detection and Subtyping with Minimal Point-Based Annotation in Whole-Slide Images
Zeyu Gao, Pargorn Puttapirat, Jiangbo Shi +1
Obtaining a large amount of labeled data in medical imaging is laborious and time-consuming, especially for histopathology. However, it is much easier and cheaper to get unlabeled…
OpenHI2 -- Open source histopathological image platform
Pargorn Puttapirat, Haichuan Zhang, Jingyi Deng +7
Transition from conventional to digital pathology requires a new category of biomedical informatic infrastructure which could facilitate delicate pathological routine. Pathological…
Effects of annotation granularity in deep learning models for histopathological images
Jiangbo Shi, Zeyu Gao, Haichuan Zhang +4
Pathological is crucial to cancer diagnosis. Usually, Pathologists draw their conclusion based on observed cell and tissue structure on histology slides. Rapid development in machi…
Efficient methods to determine the reversibility of general 1D linear cellular automata in polynomial complexity
Xinyu Du, Chao Wang, Tianze Wang +1
In this paper, we study reversibility of one-dimensional(1D) linear cellular automata(LCA) under null boundary condition, whose core problems have been divided into two main parts:…