4 papers
PathoSCOPE: Few-Shot Pathology Detection via Self-Supervised Contrastive Learning and Pathology-Informed Synthetic Embeddings
Sinchee Chin, Yinuo Ma, Xiaochen Yang +2
Unsupervised pathology detection trains models on non-pathological data to flag deviations as pathologies, offering strong generalizability for identifying novel diseases and avoid…
VISTA: Unsupervised 2D Temporal Dependency Representations for Time Series Anomaly Detection
Sinchee Chin, Fan Zhang, Xiaochen Yang +5
Time Series Anomaly Detection (TSAD) is essential for uncovering rare and potentially harmful events in unlabeled time series data. Existing methods are highly dependent on clean,…
CONSULT: Contrastive Self-Supervised Learning for Few-shot Tumor Detection
Sin Chee Chin, Xuan Zhang, Lee Yeong Khang +1
Artificial intelligence aids in brain tumor detection via MRI scans, enhancing the accuracy and reducing the workload of medical professionals. However, in scenarios with extremely…
RICASSO: Reinforced Imbalance Learning with Class-Aware Self-Supervised Outliers Exposure
Xuan Zhang, Sin Chee Chin, Tingxuan Gao +1
In real-world scenarios, deep learning models often face challenges from both imbalanced (long-tailed) and out-of-distribution (OOD) data. However, existing joint methods rely on r…