276 citations · 356 across the 8 of their papers we have counts for
5 papers · 1 filter
Consistency-guided Meta-Learning for Bootstrapping Semi-Supervised Medical Image Segmentation
Qingyue Wei, Lequan Yu, Xianhang Li +4
Medical imaging has witnessed remarkable progress but usually requires a large amount of high-quality annotated data which is time-consuming and costly to obtain. To alleviate this…
Image Classification using Graph Neural Network and Multiscale Wavelet Superpixels
Varun Vasudevan, Maxime Bassenne, Md Tauhidul Islam +1
Prior studies using graph neural networks (GNNs) for image classification have focused on graphs generated from a regular grid of pixels or similar-sized superpixels. In the latter…
CIM: Class-Irrelevant Mapping for Few-Shot Classification
Shuai Shao, Lei Xing, Yixin Chen +3
Few-shot classification (FSC) is one of the most concerned hot issues in recent years. The general setting consists of two phases: (1) Pre-train a feature extraction model (FEM) wi…
MHFC: Multi-Head Feature Collaboration for Few-Shot Learning
Shuai Shao, Lei Xing, Yan Wang +4
Few-shot learning (FSL) aims to address the data-scarce problem. A standard FSL framework is composed of two components: (1) Pre-train. Employ the base data to generate a CNN-based…
A Geometry-Informed Deep Learning Framework for Ultra-Sparse 3D Tomographic Image Reconstruction
Liyue Shen, Wei Zhao, Dante Capaldi +2
Deep learning affords enormous opportunities to augment the armamentarium of biomedical imaging, albeit its design and implementation have potential flaws. Fundamentally, most deep…