most citedPCCT: Progressive Class-Center Triplet Loss for Imbalanced Medical Image Classification

1 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024

EvLight++: Low-Light Video Enhancement with an Event Camera: A Large-Scale Real-World Dataset, Novel Method, and More

Kanghao Chen, Guoqiang Liang, Hangyu Li +2

Event cameras offer significant advantages for low-light video enhancement, primarily due to their high dynamic range. Current research, however, is severely limited by the absence…

cs.CV20241 cited

LaSe-E2V: Towards Language-guided Semantic-Aware Event-to-Video Reconstruction

Kanghao Chen, Hangyu Li, JiaZhou Zhou +2

Event cameras harness advantages such as low latency, high temporal resolution, and high dynamic range (HDR), compared to standard cameras. Due to the distinct imaging paradigm shi…

cs.CV2024

EIT-1M: One Million EEG-Image-Text Pairs for Human Visual-textual Recognition and More

Xu Zheng, Ling Wang, Kanghao Chen +3

Recently, electroencephalography (EEG) signals have been actively incorporated to decode brain activity to visual or textual stimuli and achieve object recognition in multi-modal A…

cs.CV2024

Towards Robust Event-guided Low-Light Image Enhancement: A Large-Scale Real-World Event-Image Dataset and Novel Approach

Guoqiang Liang, Kanghao Chen, Hangyu Li +2

Event camera has recently received much attention for low-light image enhancement (LIE) thanks to their distinct advantages, such as high dynamic range. However, current research i…

cs.CV20221 cited

PCCT: Progressive Class-Center Triplet Loss for Imbalanced Medical Image Classification

Kanghao Chen, Weixian Lei, Rong Zhang +3

Imbalanced training data is a significant challenge for medical image classification. In this study, we propose a novel Progressive Class-Center Triplet (PCCT) framework to allevia…