5 citations · 9 across the 7 of their papers we have counts for
7 papers
SonicSieve: Bringing Directional Speech Extraction to Smartphones Using Acoustic Microstructures
Kuang Yuan, Yifeng Wang, Xiyuxing Zhang +3
Imagine placing your smartphone on a table in a noisy restaurant and clearly capturing the voices of friends seated around you, or recording a lecturer's voice with clarity in a re…
HEPHA: A Mixed-Initiative Image Labeling Tool for Specialized Domains
Shiyuan Zhou, Bingxuan Li, Xiyuan Chen +4
Image labeling is an important task for training computer vision models. In specialized domains, such as healthcare, it is expensive and challenging to recruit specialists for imag…
AutoAL: Automated Active Learning with Differentiable Query Strategy Search
Yifeng Wang, Xueying Zhan, Siyu Huang
As deep learning continues to evolve, the need for data efficiency becomes increasingly important. Considering labeling large datasets is both time-consuming and expensive, active…
DS-ViT: Dual-Stream Vision Transformer for Cross-Task Distillation in Alzheimer's Early Diagnosis
Ke Chen, Yifeng Wang, Yufei Zhou +1
In the field of Alzheimer's disease diagnosis, segmentation and classification tasks are inherently interconnected. Sharing knowledge between models for these tasks can significant…
From Tissue Plane to Organ World: A Benchmark Dataset for Multimodal Biomedical Image Registration using Deep Co-Attention Networks
Yifeng Wang, Weipeng Li, Thomas Pearce +1
Correlating neuropathology with neuroimaging findings provides a multiscale view of pathologic changes in the human organ spanning the meso- to micro-scales, and is an emerging met…
ADAPT: Alzheimer Diagnosis through Adaptive Profiling Transformers
Yifeng Wang, Ke Chen, Haohan Wang
Automated diagnosis of Alzheimer Disease(AD) from brain imaging, such as magnetic resonance imaging (MRI), has become increasingly important and has attracted the community to cont…
Rapid Image Labeling via Neuro-Symbolic Learning
Yifeng Wang, Zhi Tu, Yiwen Xiang +4
The success of Computer Vision (CV) relies heavily on manually annotated data. However, it is prohibitively expensive to annotate images in key domains such as healthcare, where da…