Quantitative evaluation methods for water-flooded layers of conglomerate reservoir based on well logging data The rapid changing near source, multi-stream depositional environment of conglomerate reservoirs leads to severe heterogeneity, complex lithology and physi... F Tan,H Li,C Xu,... - 《石油科...
Sol-Gel Preparation of Zn_2 SiO_4: Mn Phosphor Layers on Silica Spheres and Their Luminescent Properties The synthesis and luminescence properties of Zn_2SiO_4: Mn phosphor layers on spherical silica spheres, i. e. , a kind of core-shell complex phosphor, Zn_2... D Kong,M Yu,C Lin...
Compounds are provided for use in assays of organic compounds, where organic compounds of biological interest are determined at extremely low concentrations by combining in a medium, the composition to be determined, hereinafter referred to as ligand, a high molecular weight material of at least 10...
Globally, peatlands have been recognized as important carbon sinks while only covering approximately 3% of the earth’s land surface. Root exudates are known key drivers of C cycling in soils and rhizosphere priming effects have been studied extensively in terrestrial ecosystems. Their role for decom...
The maximum pool layers and batch normalization layers are set after the convolution layer, which can reduce the size of the model and improve the calculation speed. Finally, the dimension of the data is transformed by using the flatten layer, and the data are sent to the Softmax layer for...
PolSAR image classification methods have been widely studied in the past decades, but due to the limited performance of the features and classifiers used, the generality and reliability of the traditional methods are still not enough to meet the needs of many practical applications. In recent years...
Tremendous progress has been made in object recognition with deep convolutional neural networks (CNNs), thanks to the availability of large-scale annotated dataset. With the ability of learning highly hierarchical image feature extractors, deep CNNs are
Typically, a CNN framework processes the raw image through a certain number of convolutional layers and outputs the image’s feature maps at the last convolutional layer. Specifically, a convolutional layer processes the image using shared convolution kernels, which are able to retain the spatial ...