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。 MS-D网络结构示意图(图片来自论文
In spite of the fact that convolutional neural network-based stereo matching models have shown good performance in both accuracy and robustness, the issue of image feature loss in regions of texture-less, complex scenes and occlusions remains. In this paper, we present a dense convolutional neural...
To solve these problems, in this paper, we propose a two-stage real-time video smoke detection method base on dense optical flow and convolutional neural network. In the first stage, we propose a fast pre-positioning module to obtain suspicious smoke areas through the dynamic characteristics of...
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 ...
Dense Residual Convolutional Neural Network based In-Loop Filter(DRNLF),程序员大本营,技术文章内容聚合第一站。
We trained a convolutional neural network29 (Supplementary Fig. 4a) on paired low- and high-SNR imaging volumes from extracellularly labeled mouse organotypic hippocampal slice cultures and the alveus region of acutely prepared mouse hippocampus. These were sampled at high SNR with 70 µs voxel...
Dense-CNN: Dense convolutional neural network for stereo matching using multiscale feature connection Signal Processing: Image Communication Volume 95,July 2021, Page 116285 Purchase options CorporateFor R&D professionals working in corporate organizations. ...
The aim of this paper is to improve the performance of different affective EEG-based PI using a channel attention mechanism of convolutional neural dense connection network (CADCNN net) approach. Channel attention mechanism (CA) is used to handle the channel information from the EEG, while ...
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-...
High-Dimensional Dense Residual Convolutional Neural Network for Light Field Reconstruction - monaen/LightFieldReconstruction