4 papers
Efficient Fourier Filtering Network with Contrastive Learning for AAV-based Unaligned Bimodal Salient Object Detection
Pengfei Lyu, Pak-Hei Yeung, Xiaosheng Yu +3
Autonomous aerial vehicle (AAV)-based bi-modal salient object detection (BSOD) aims to segment salient objects in a scene utilizing complementary cues in unaligned RGB and thermal…
Deep Fourier-embedded Network for RGB and Thermal Salient Object Detection
Pengfei Lyu, Xiaosheng Yu, Pak-Hei Yeung +2
The rapid development of deep learning has significantly improved salient object detection (SOD) combining both RGB and thermal (RGB-T) images. However, existing Transformer-based…
Weakly Supervised Segmentation Framework for Thyroid Nodule Based on High-confidence Labels and High-rationality Losses
Jianning Chi, Zelan Li, Geng Lin +2
Weakly supervised segmentation methods can delineate thyroid nodules in ultrasound images efficiently using training data with coarse labels, but suffer from: 1) low-confidence pse…
Bridging the Inter-Domain Gap through Low-Level Features for Cross-Modal Medical Image Segmentation
Pengfei Lyu, Pak-Hei Yeung, Xiaosheng Yu +4
This paper addresses the task of cross-modal medical image segmentation by exploring unsupervised domain adaptation (UDA) approaches. We propose a model-agnostic UDA framework, Low…