32 citations · 35 across the 8 of their papers we have counts for
8 papers
Memory-Augmented Online Test-Time Adaptation for EEG Motor Imagery via Perturbation Consistency and Confidence Calibration
Kunkun Zhang, Kehao Wu, Zhitao Chen +2
Recently, electroencephalography (EEG)-based brain--computer interfaces (BCIs) have gained traction as portable neural measurement systems. However, the practical deployment of the…
MaskAnyNet: Rethinking Masked Image Regions as Valuable Information in Supervised Learning
Jingshan Hong, Haigen Hu, Huihuang Zhang +2
In supervised learning, traditional image masking faces two key issues: (i) discarded pixels are underutilized, leading to a loss of valuable contextual information; (ii) masking m…
IAFI-FCOS: Intra- and across-layer feature interaction FCOS model for lesion detection of CT images
Qiu Guan, Mengjie Pan, Feng Chen +4
Effective lesion detection in medical image is not only rely on the features of lesion region,but also deeply relative to the surrounding information.However,most current methods h…
LSM-YOLO: A Compact and Effective ROI Detector for Medical Detection
Zhongwen Yu, Qiu Guan, Jianmin Yang +4
In existing medical Region of Interest (ROI) detection, there lacks an algorithm that can simultaneously satisfy both real-time performance and accuracy, not meeting the growing de…
DuEDL: Dual-Branch Evidential Deep Learning for Scribble-Supervised Medical Image Segmentation
Yitong Yang, Xinli Xu, Haigen Hu +3
Despite the recent progress in medical image segmentation with scribble-based annotations, the segmentation results of most models are still not ro-bust and generalizable enough in…
Deep Co-supervision and Attention Fusion Strategy for Automatic COVID-19 Lung Infection Segmentation on CT Images
Haigen Hu, Leizhao Shen, Qiu Guan +3
Due to the irregular shapes,various sizes and indistinguishable boundaries between the normal and infected tissues, it is still a challenging task to accurately segment the infecte…
Adaptively Customizing Activation Functions for Various Layers
Haigen Hu, Aizhu Liu, Qiu Guan +3
To enhance the nonlinearity of neural networks and increase their mapping abilities between the inputs and response variables, activation functions play a crucial role to model mor…
TaskDrop: A Competitive Baseline for Continual Learning of Sentiment Classification
Jianping Mei, Yilun Zheng, Qianwei Zhou +1
In this paper, we study the multi-task sentiment classification problem in the continual learning setting, i.e., a model is sequentially trained to classifier the sentiment of revi…