… Intrusion detection of moving targets at sea based on visible video is a very important
research topic. In this paper, the research status of moving target detection and recognition is …

… score, MOS),平均主观得分 差异(Dierential mean opinion score, DMOS),均 方误差(Mean
square error, MSE),结构相似性 (Structural similarity index, SSIM),多尺度结构 相似性(Multi-scale …

… deep convolutional neural networks[C]//Proceedings of the 25th International Conference
on Neural … Multi-scale context aggregation by dilated convolutions[Z]. arXiv: 1511.07122[cs:CV]…

… At the same time, a plenty of deep learning models showed their powerful … as Deep
Convolutional Neural Network, Deep Recurrent Neural Network, Deep Belief Network and Deep …

… Traffic sign recognition method based on multi-layer feature CNN and extreme learning
machine[J]. Journal of University of Electronic Science and Technology of China, 2018, 47(3):343…

… ability of network intrusion detection model, an intrusion detection … , or deep learning
methods such as stacked denoising autoencoder and multi-scale convolution neural network. …

… we introduce a novel deep learning model tailored for erosion gully recognition based on
a multi-scale dense dilated convolutional neural network. Our model incorporates dense …

… Steganalysis is an effective way of detecting secret … algorithm based on multi-scale residual
convolution network, mainly … part, residual convolution layer, multi-scale residual convolution …

… convolution filters effectively. Compared with the traditional multi-scale convolution kernel,
proposed method has higher computational efficiency and better accuracy. Experimental …

… network of multi-scale analysis with deep threshold noise elimination to recognize the actually
collected modulated signals under a symmetric cross-entropy function of label smoothing. …