In this research work, a novel dense Convolutional Neural Network (CNN) based deep learning model is proposed to accurately detect benign and malignant tumour classes using Wisconsin Breast Cancer dataset. The performance metrics such as accuracy, sensitivity, precision, F1-score, a...
In this paper, we presented a novel MR image SR method based on a dense convolutional neural network (DDSR), and its enhanced version called EDDSR. There are three major innovations: first, we re-designed dense modules to extract hierarchical features directly from LR images and propagate the...
Deep neural networks (DNNs) have emerged as a relevant tool for the classification of remotely sensed hyperspectral images (HSIs), with convolutional neural networks (CNNs) being the current state-of-the-art in many classification tasks. However, deep CNNs present several limitations in the conte...
Ye et al.8 proposed a self-supervised learning framework for a monocular depth estimation Convolutional Neural Network (CNN) model, which is an improved version of DeConvNet19. They used the disparity information obtained by a classical stereo algorithm from a stereo image pair as a self-...
为了解决这些问题,此文[1]结合了扩张卷积 (dilated convolution) 和密集连接 (dense connection),提出了Mixed-Scale Dense Convolutional Network (MS-D网络),MS-D网络和传统的DCNN相比,提高了特征提取、特征传递的能力,在样本少的情况下,也获得了很好的效果。
Complex neural network such as Deep Neural Networks (DNNs) or Convolutional Neural Networks (CNNs) without PMF can increase an accuracy of a sensor model to a satisfied level18 but our more simple SDNN with PMF, the higher accuracy could be achieved. CNNs and DNNs without PMF were proven ...
High-Dimensional Dense Residual Convolutional Neural Network for Light Field Reconstruction 来自 NCBI 喜欢 0 阅读量: 116 作者:N Meng,KH So,X Sun,EY Lam 摘要: We consider the problem of high-dimensional light field reconstruction and develop a learning-based framework for spatial and angular super...
High-Dimensional Dense Residual Convolutional Neural Network for Light Field Reconstruction - monaen/LightFieldReconstruction
关键词：冠状动脉血管；图像分割；U-Dense~ne t;密集残差块；注意力机制；深度神经网络；DSA 中图分类号：TS391.4 文献标志码：A 文章编号：1673-3851 (2021) O5-O39(M0 Coronary artery segmentation of DSA images based on U-Dense-net network WANG Zhuoyi?jg], TONG Jiju n1 •,JIA N G Lurong]...
WebCNN is a browser-based Convolutional Neural Network framework. This is a personal project in the earliest stages of development, which I'm sharing publicly for those with academic interest. I have a live demo for the MNIST classification here: http://www.denseinl2.com/webcnn/digitdemo.ht...