A Novel Automation-Assisted Cervical Cancer Reading Method Based on Convolutional Neural Network

no code implementations • 14 Dec 2019 • Yao Xiang, Wanxin Sun, Changli Pan, Meng Yan, Zhihua Yin, Yixiong Liang

Our model achieves 97. 5% sensitivity (Sens) and 67. 8% specificity (Spec) on cervical cell image-level screening.

Cell Segmentation object-detection +2

Scale-Invariant Structure Saliency Selection for Fast Image Fusion

1 code implementation • 30 Oct 2018 • Yixiong Liang, Yuan Mao, Jiazhi Xia, Yao Xiang, Jianfeng Liu

Specifically, we propose a scale-invariant structure saliency selection scheme based on the difference-of-Gaussian (DoG) pyramid of images to build the weights or activity map.

Comparison-Based Convolutional Neural Networks for Cervical Cell/Clumps Detection in the Limited Data Scenario

1 code implementation • 14 Oct 2018 • Yixiong Liang, Zhihong Tang, Meng Yan, Jialin Chen, Qing Liu, Yao Xiang

In this paper we propose an efficient CNN-based object detection methods for cervical cancer cells/clumps detection.

Cell Segmentation Few-Shot Learning +2

Feature Selection via Sparse Approximation for Face Recognition

no code implementations • 14 Feb 2011 • Yixiong Liang, Lei Wang, Yao Xiang, Beiji Zou

Inspired by biological vision systems, the over-complete local features with huge cardinality are increasingly used for face recognition during the last decades.

Face Recognition feature selection