Sijia Li

DeepGaitLab: Accurate and Flexible Markerless Motion Tracking Powered by Synthetic Data

Eni Halilaj, Soyong Shin, Sijia Li, Zhixiong Li, Anastasios Yiannakidis, Hanz Cuevas Velasquez, et al.

CDR-Bench: Evaluating Faithful Execution of Compositional, Order-Sensitive Data Refinement Recipes

Yuchen Huang, Xiang Li, Zhenqing Ling, Sijia Li, Qianli Shen, Daoyuan Chen, et al.

Data refinement involves executing multi-step recipes over evolving text states, where both composition and execution order of processing operators determine the outcome. While existing benchmarks either isolate text editing or entangle it with code and tool execution, it remains…Read more

CW-B: Class Weighted Boosting Framework for Imbalance Resilient Multi Class Cardiac Phenotyping

Sijia Li, Xiaoyu Tan, Chen Zhan, Yuanji Ma, Haoyu Wang, Xihe Qiu

Cardiac discharge phenotyping informs post-discharge treatment and follow-up, but real-world records are often incomplete and class-imbalanced, increasing the risk of missed high-risk phenotypes. We propose CW-B, a clinical risk-aligned class-weighted XGBoost pipeline for five-cl…Read more

Individual Tree-Level Biomass Mapping in Chinese Coniferous Plantation Forests Using Multimodal UAV Remote Sensing Approach Integrating Deep Learning and Machine Learning

Yiru Wang, Zhaohua Liu, Jiping Li, Hui Lin, Jiangping Long, Guangyi Mu, et al.

Accurate estimation of individual tree aboveground biomass (AGB) is essential for understanding forest carbon dynamics, optimizing resource management, and addressing climate change. Conventional methods rely on destructive sampling, whereas unmanned aerial vehicle (UAV) remote s…Read more

A review of machine learning applications in inland and nearshore water color remote sensing: from preprocessing to object detection and parameter estimation

Jiarui Shi, Zuchuan Li, Ge Liu, C. Fang, Z. Wen, Y. Shang, et al.