57 citations · 63 across the 6 of their papers we have counts for
7 papers
Predicting Adverse Neonatal Outcomes for Preterm Neonates with Multi-Task Learning
Jingyang Lin, Junyu Chen, Hanjia Lyu +6
Diagnosis of adverse neonatal outcomes is crucial for preterm survival since it enables doctors to provide timely treatment. Machine learning (ML) algorithms have been demonstrated…
VideoXum: Cross-modal Visual and Textural Summarization of Videos
Jingyang Lin, Hang Hua, Ming Chen +4
Video summarization aims to distill the most important information from a source video to produce either an abridged clip or a textual narrative. Traditionally, different methods h…
Out-of-Distribution Detection with Hilbert-Schmidt Independence Optimization
Jingyang Lin, Yu Wang, Qi Cai +4
Outlier detection tasks have been playing a critical role in AI safety. There has been a great challenge to deal with this task. Observations show that deep neural network classifi…
Improving Self-supervised Learning with Automated Unsupervised Outlier Arbitration
Yu Wang, Jingyang Lin, Jingjing Zou +3
Our work reveals a structured shortcoming of the existing mainstream self-supervised learning methods. Whereas self-supervised learning frameworks usually take the prevailing perfe…
CORE-Text: Improving Scene Text Detection with Contrastive Relational Reasoning
Jingyang Lin, Yingwei Pan, Rongfeng Lai +3
Localizing text instances in natural scenes is regarded as a fundamental challenge in computer vision. Nevertheless, owing to the extremely varied aspect ratios and scales of text…
A Low Rank Promoting Prior for Unsupervised Contrastive Learning
Yu Wang, Jingyang Lin, Qi Cai +4
Unsupervised learning is just at a tipping point where it could really take off. Among these approaches, contrastive learning has seen tremendous progress and led to state-of-the-a…
Improving Fast Segmentation With Teacher-student Learning
Jiafeng Xie, Bing Shuai, Jian-Fang Hu +2
Recently, segmentation neural networks have been significantly improved by demonstrating very promising accuracies on public benchmarks. However, these models are very heavy and ge…