Nanjing University of Information Science and Technology

About: Nanjing University of Information Science and Technology is a education organization based out in Nanjing, China. It is known for research contribution in the topics: Precipitation & Aerosol. The organization has 14129 authors who have published 17985 publications receiving 267578 citations. The organization is also known as: Nan Xin Da.

Hyperspectral Image Classification Using Spectral-Spatial LSTMs

Abstract: In this paper, we propose a hyperspectral image (HSI) classification method using spectral-spatial long short term memory (LSTM) networks. Specifically, for each pixel, we feed its spectral values in different channels into Spectral LSTM one by one to learn the spectral feature. Meanwhile, we firstly use principle component analysis (PCA) to extract the first principle component from a HSI, and then select local image patches centered at each pixel from it. After that, we feed the row vectors of each image patch into Spatial LSTM one by one to learn the spatial feature for the center pixel. In the classification stage, the spectral and spatial features of each pixel are fed into softmax classifiers respectively to derive two different results, and a decision fusion strategy is further used to obtain a joint spectral-spatial results. Experiments are conducted on two widely used HSIs, and the results show that our method can achieve higher performance than other state-of-the-art methods.

Partitioned-cooperative quantum-behaved particle swarm optimization based on multilevel thresholding applied to medical image segmentation

Abstract: Display Omitted We introduce a novel quantum-behaved particle swarm optimization (SCQPSO) algorithm- SCQPSO.In SCQPSO, the auxiliary swarms and partitioned search space are introduced to increase the population diversity.In SCQPSO, the cooperative theory is introduced into QPSO algorithm to change the updating mode of the particles.SCQPSO is tested on five benchmark test functions and five shift complex functions.We use SCQPSO to optimize the parameters for OTSU image segmentation of four stomach CT images. In this paper, in order to search the global optimum solution with a very fast convergence speed across the whole search space, we propose a partitioned and cooperative quantum-behaved particle swarm optimization (SCQPSO) algorithm. The auxiliary swarms and partitioned search space are introduced to increase the population diversity. The cooperative theory is introduced into QPSO algorithm to change the updating mode of the particles in order to guarantee that this algorithm well balances the effectiveness and simplification. Firstly, we explain how this method leads to enhanced population diversity and improved algorithm over previous strategies, and emphasize this algorithm with comparative experiments using five benchmark test functions and five shift complex functions. After that we demonstrate a reasonable application of the proposed algorithm, by showing how it can be used to optimize the parameters for OTSU image segmentation for processing medical images. The results show that the proposed SCQPSO algorithm outperforms than the other improved QPSO in terms of the quality of the solution, and performs better for solving the image segmentation than the QPSO algorithm, the sunCQPSO algorithm, the CCQPSO algorithm.

Mean residence time of global topsoil organic carbon depends on temperature, precipitation and soil nitrogen

Abstract: Mean residence time (MRT) of topsoil organic carbon is one critical parameter for predicting future land carbon sink dynamics Large uncertainties remain about controls on the variability in global MRT of soil organic carbon We estimated global MRT of topsoil (0–20 cm) organic carbon in terrestrial ecosystems and found that mean annual air temperature, annual precipitation, and topsoil nitrogen storage were responsible for the variability in MRT An empirical climate and soil nitrogen-based (Clim&SN) model could be used to explain the temporal and spatial variability in MRT across various ecosystems Estimated MRT was lowest in the low-latitude zones, and increased toward high-latitude zones Global MRT of topsoil organic carbon showed a significant declining tendency between 1960 and 2008, particularly in the high-latitude zone of the northern hemisphere The largest absolute and relative changes (02% per yr) in MRT of topsoil organic carbon from 1960 to 2008 occurred in high-latitude regions, consistent with large carbon stocks in, and greater degree of climate change being experienced by, these areas Overall, global MRT anomalies (differences between MRT in each year and averaged value of MRT from 1960 to 2008) of terrestrial topsoil organic carbon were decreasing from 1960 to 2008 Global MRT anomalies decreased significantly (P