6 papers
Rethinking Medical Anomaly Detection in Brain MRI: An Image Quality Assessment Perspective
Zixuan Pan, Jun Xia, Zheyu Yan +7
Reconstruction-based methods, particularly those leveraging autoencoders, have been widely adopted for anomaly detection task in brain MRI. Unlike most existing works try to improv…
Contrastive Learning with Diffusion Features for Weakly Supervised Medical Image Segmentation
Dewen Zeng, Xinrong Hu, Yu-Jen Chen +3
Weakly supervised semantic segmentation (WSSS) methods using class labels often rely on class activation maps (CAMs) to localize objects. However, traditional CAM-based methods str…
EdgeOL: Efficient in-situ Online Learning on Edge Devices
Sheng Li, Geng Yuan, Yue Dai +10
Emerging applications, such as robot-assisted eldercare and object recognition, generally employ deep learning neural networks (DNNs) and naturally require: i) handling streaming-i…
Contrastive Learning with Synthetic Positives
Dewen Zeng, Yawen Wu, Xinrong Hu +2
Contrastive learning with the nearest neighbor has proved to be one of the most efficient self-supervised learning (SSL) techniques by utilizing the similarity of multiple instance…
DLF: Disentangled-Language-Focused Multimodal Sentiment Analysis
Pan Wang, Qiang Zhou, Yawen Wu +2
Multimodal Sentiment Analysis (MSA) leverages heterogeneous modalities, such as language, vision, and audio, to enhance the understanding of human sentiment. While existing models…
Enhancing 3D Transformer Segmentation Model for Medical Image with Token-level Representation Learning
Xinrong Hu, Dewen Zeng, Yawen Wu +2
In the field of medical images, although various works find Swin Transformer has promising effectiveness on pixelwise dense prediction, whether pre-training these models without us…