Timely and accurate population statistic data plays an important role in many fields.To illustrate the demographic characteristics,population density is a crucial factor in evaluating population data.With a dynamic re...Timely and accurate population statistic data plays an important role in many fields.To illustrate the demographic characteristics,population density is a crucial factor in evaluating population data.With a dynamic regional migration in population,it is a challenging job to evaluate population density without a census-based survey.We present the approach to classify satellite images in different magnitudes in population density and execute the comparative experiment to discuss the factors that influence the identification to the images with the deep learning approach.In this paper,we use satellite imagery and community population density data.With convolutional neural networks,we evaluated the performance of CNN on population estimation with satellite images,found the features that are important in population estimation,and then perform the sensitive analysis.展开更多
A layered compression algorithm is presented which delivers spatial scalable encoded bit streams for remote video monitoring system. The complexity of the algorithm is modest and is well suited to real time implementa...A layered compression algorithm is presented which delivers spatial scalable encoded bit streams for remote video monitoring system. The complexity of the algorithm is modest and is well suited to real time implementation. Based on the layered compression algorithm, a codec system model is established. High-speed video compression can be realized with parallel data compression in this codec system. For image reconstruction, a prediction method using two nearest pix points is presented.展开更多
Association rule mining is an important issue in data mining. The paper proposed an binary system based method to generate candidate frequent itemsets and corresponding supporting counts efficiently, which needs only ...Association rule mining is an important issue in data mining. The paper proposed an binary system based method to generate candidate frequent itemsets and corresponding supporting counts efficiently, which needs only some operations such as ＂and＂, ＂or＂ and ＂xor＂. Applying this idea in the existed distributed association rule mining al gorithm FDM, the improved algorithm BFDM is proposed. The theoretical analysis and experiment testify that BFDM is effective and efficient.展开更多
文摘Timely and accurate population statistic data plays an important role in many fields.To illustrate the demographic characteristics,population density is a crucial factor in evaluating population data.With a dynamic regional migration in population,it is a challenging job to evaluate population density without a census-based survey.We present the approach to classify satellite images in different magnitudes in population density and execute the comparative experiment to discuss the factors that influence the identification to the images with the deep learning approach.In this paper,we use satellite imagery and community population density data.With convolutional neural networks,we evaluated the performance of CNN on population estimation with satellite images,found the features that are important in population estimation,and then perform the sensitive analysis.
文摘A layered compression algorithm is presented which delivers spatial scalable encoded bit streams for remote video monitoring system. The complexity of the algorithm is modest and is well suited to real time implementation. Based on the layered compression algorithm, a codec system model is established. High-speed video compression can be realized with parallel data compression in this codec system. For image reconstruction, a prediction method using two nearest pix points is presented.
基金Supported by the National Natural Science Foun-dation of China (70371015)
文摘Association rule mining is an important issue in data mining. The paper proposed an binary system based method to generate candidate frequent itemsets and corresponding supporting counts efficiently, which needs only some operations such as ＂and＂, ＂or＂ and ＂xor＂. Applying this idea in the existed distributed association rule mining al gorithm FDM, the improved algorithm BFDM is proposed. The theoretical analysis and experiment testify that BFDM is effective and efficient.
