For anomaly detection,anomalies existing in the background will affect the detection performance.Accordingly,a background refinement method based on the local density is proposed to remove the anomalies from thebackgr...For anomaly detection,anomalies existing in the background will affect the detection performance.Accordingly,a background refinement method based on the local density is proposed to remove the anomalies from thebackground.In this work,the local density is measured by its spectral neighbors through a certain radius which is obtained by calculating the mean median of the distance matrix.Further,a two-step segmentation strategy is designed.The first segmentation step divides the original background into two subsets,a large subset composed by background pixels and a small subset containing both background pixels and anomalies.The second segmentation step employing Otsu method with an aim to obtain a discrimination threshold is conducted on the small subset.Then the pixels whose local densities are lower than the threshold are removed.Finally,to validate the effectiveness of the proposed method,it combines Reed-Xiaoli detector and collaborative-representation-based detector to detect anomalies.Experiments are conducted on two real hyperspectral datasets.Results show that the proposed method achieves better detection performance.展开更多
Fostering the use of transit has been broadly accepted as an effective way to improve social equity and reduce the externalities caused by transportation. In the great body of transit literature, many have focused on ...Fostering the use of transit has been broadly accepted as an effective way to improve social equity and reduce the externalities caused by transportation. In the great body of transit literature, many have focused on the improvement of transfer efficiency. However, investigation on transit transfer efficiency is still lacking for medium sized cities or suburban areas that have sprawled from city centers. The special features associated with such an urban form lead to unique travel patterns and bus operations. This work develops a process to improve bus transfer efficiency for small conurbations considering their special characteristics. A case study of New York's Capital District is used to illustrate the proposed method. Results show that the transfer waiting time can be remarkably shortened. The proposed method can be widely adapted to other transit systems in small conurbations.展开更多
基金Projects(61405041,61571145)supported by the National Natural Science Foundation of ChinaProject(ZD201216)supported by the Key Program of Heilongjiang Natural Science Foundation,China+1 种基金Project(RC2013XK009003)supported by Program Excellent Academic Leaders of Harbin,ChinaProject(HEUCF1508)supported by the Fundamental Research Funds for the Central Universities,China
文摘For anomaly detection,anomalies existing in the background will affect the detection performance.Accordingly,a background refinement method based on the local density is proposed to remove the anomalies from thebackground.In this work,the local density is measured by its spectral neighbors through a certain radius which is obtained by calculating the mean median of the distance matrix.Further,a two-step segmentation strategy is designed.The first segmentation step divides the original background into two subsets,a large subset composed by background pixels and a small subset containing both background pixels and anomalies.The second segmentation step employing Otsu method with an aim to obtain a discrimination threshold is conducted on the small subset.Then the pixels whose local densities are lower than the threshold are removed.Finally,to validate the effectiveness of the proposed method,it combines Reed-Xiaoli detector and collaborative-representation-based detector to detect anomalies.Experiments are conducted on two real hyperspectral datasets.Results show that the proposed method achieves better detection performance.
文摘Fostering the use of transit has been broadly accepted as an effective way to improve social equity and reduce the externalities caused by transportation. In the great body of transit literature, many have focused on the improvement of transfer efficiency. However, investigation on transit transfer efficiency is still lacking for medium sized cities or suburban areas that have sprawled from city centers. The special features associated with such an urban form lead to unique travel patterns and bus operations. This work develops a process to improve bus transfer efficiency for small conurbations considering their special characteristics. A case study of New York's Capital District is used to illustrate the proposed method. Results show that the transfer waiting time can be remarkably shortened. The proposed method can be widely adapted to other transit systems in small conurbations.
