Pinned Repositories
CornerNet
tensorflow
FC-DenseNet
Fully Convolutional DenseNets for semantic segmentation.
Keras-GAN
Keras implementations of Generative Adversarial Networks.
matalb_learning
recoding my leraning about matalb
moves-recommend
just use it is not create by me
pythonworkbook
exercisework
Segthor19-using-ResU-net
The recent advances in the field of computer vision has led to the wide use of Convolutional Neural Networks (CNNs) in organ segmentation of computed tomography (CT) images. Image guided radiation therapy requires the accurate segmentation of organs at risk (OARs). In this paper, we propose a 2D U-Net network to automatically segment thoracic organs at risk in computed tomography (CT) images. The architecture consists of a down sampling path to capture features and a symmetric up sampling path to obtain precise localization. SegTHOR19 is a competition timed to the conference IEEE ISBI 2019 that addresses the problem of organs at risk segmentation in Computed Tomography (CT) images. In the SegTHOR19 challenge, 40 CT scans with 4 thoracic organs (i.e., esophagus, heart, trachea and aorta) were used for training [1]. We experimented with both 2D U-net and 2D U-Net with Resnet18 architecture to train the networks. Our best results were obtained by using 2D Convolutional U-Net with ResNet18.
SlimYOLOv3
This page is for the SlimYOLOv3: Narrower, Faster and Better for UAV Real-Time Applications
tensorflow-vgg16
...
unity-ugui-XCharts
A charting and data visualization library for Unity. 一款基于UGUI的数据可视化图表插件。
minghaizhang's Repositories
minghaizhang/tensorflow-vgg16
...
minghaizhang/unity-ugui-XCharts
A charting and data visualization library for Unity. 一款基于UGUI的数据可视化图表插件。
minghaizhang/CornerNet
tensorflow
minghaizhang/FC-DenseNet
Fully Convolutional DenseNets for semantic segmentation.
minghaizhang/Keras-GAN
Keras implementations of Generative Adversarial Networks.
minghaizhang/matalb_learning
recoding my leraning about matalb
minghaizhang/moves-recommend
just use it is not create by me
minghaizhang/pythonworkbook
exercisework
minghaizhang/Segthor19-using-ResU-net
The recent advances in the field of computer vision has led to the wide use of Convolutional Neural Networks (CNNs) in organ segmentation of computed tomography (CT) images. Image guided radiation therapy requires the accurate segmentation of organs at risk (OARs). In this paper, we propose a 2D U-Net network to automatically segment thoracic organs at risk in computed tomography (CT) images. The architecture consists of a down sampling path to capture features and a symmetric up sampling path to obtain precise localization. SegTHOR19 is a competition timed to the conference IEEE ISBI 2019 that addresses the problem of organs at risk segmentation in Computed Tomography (CT) images. In the SegTHOR19 challenge, 40 CT scans with 4 thoracic organs (i.e., esophagus, heart, trachea and aorta) were used for training [1]. We experimented with both 2D U-net and 2D U-Net with Resnet18 architecture to train the networks. Our best results were obtained by using 2D Convolutional U-Net with ResNet18.
minghaizhang/SlimYOLOv3
This page is for the SlimYOLOv3: Narrower, Faster and Better for UAV Real-Time Applications
minghaizhang/Test_HandWriteDititalNumber
some projects to learn and some works by myself
minghaizhang/torchcv
A PyTorch-Based Framework for Deep Learning in Computer Vision
minghaizhang/Unity3DTraining
Unity的练习项目