1 citations · 3 across the 8 of their papers we have counts for
8 papers
Shape-Margin Knowledge Augmented Network for Thyroid Nodule Segmentation and Diagnosis
Weihua Liu, Chaochao Lin
Thyroid nodule segmentation is a crucial step in the diagnostic procedure of physicians and computer-aided diagnosis systems. Mostly, current studies treat segmentation and diagnos…
Enhancing Mobile Face Anti-Spoofing: A Robust Framework for Diverse Attack Types under Screen Flash
Weihua Liu, Chaochao Lin, Yu Yan
Face anti-spoofing (FAS) is crucial for securing face recognition systems. However, existing FAS methods with handcrafted binary or pixel-wise labels have limitations due to divers…
Occlusion-Aware Deep Convolutional Neural Network via Homogeneous Tanh-transforms for Face Parsing
Jianhua Qiua, Weihua Liu, Chaochao Lin +3
Face parsing infers a pixel-wise label map for each semantic facial component. Previous methods generally work well for uncovered faces, however, they overlook facial occlusion and…
Stone Needle: A General Multimodal Large-scale Model Framework towards Healthcare
Weihua Liu, Yong Zuo
In healthcare, multimodal data is prevalent and requires to be comprehensively analyzed before diagnostic decisions, including medical images, clinical reports, etc. However, curre…
A Novel Structured Natural Gradient Descent for Deep Learning
Weihua Liu, Xiabi Liu
Natural gradient descent (NGD) provided deep insights and powerful tools to deep neural networks. However the computation of Fisher information matrix becomes more and more difficu…
PiaNet: A pyramid input augmented convolutional neural network for GGO detection in 3D lung CT scans
Weihua Liu, Xiabi Liua, Xiongbiao Luo +4
This paper proposes a new convolutional neural network with multiscale processing for detecting ground-glass opacity (GGO) nodules in 3D computed tomography (CT) images, which is r…
Contraction Mapping of Feature Norms for Classifier Learning on the Data with Different Quality
Weihua Liu, Xiabi Liu, Murong Wang +1
The popular softmax loss and its recent extensions have achieved great success in the deep learning-based image classification. However, the data for training image classifiers usu…
A New Three-stage Curriculum Learning Approach to Deep Network Based Liver Tumor Segmentation
Huiyu Li, Xiabi Liu, Said Boumaraf +3
Automatic segmentation of liver tumors in medical images is crucial for the computer-aided diagnosis and therapy. It is a challenging task, since the tumors are notoriously small a…