False anomaly recognition with horizontal differential field lines method in high-density electrical technique and its application in Xinlei Quarry,Jiuquan

As an important geophysical tool,high density electrical technique infers the underground geological structures by processing and inverting the apparent resistivity data.Currently,the false anomalies have been frequently occurred in the graph of apparent resistivity pseudo-section or inverted geoelectrical section obtained from high-density electrical technique,and are difficult to remove.In this study,the authors explain the mechanism of the false anomalies and put forward the horizontal differential field method to identify the false anomalies.Based on the analysis of modeling results,this method is applied in the surveying data in Xinlei Quarry of Jiuquan,and the results confirm the effectiveness of the horizontal differential field method.

Multi-angle Face Detection Based on DP-Adaboost

Although important progresses have been already made in face detection,many false faces can be found in detection results and false detection rate is influenced by some factors,such as rotation and tilt of human face,complicated background,illumination,scale,cloak and hairstyle.This paper proposes a new method called DP-Adaboost algorithm to detect multi-angle human face and improve the correct detection rate.An improved Adaboost algorithm with the fusion of frontal face classifier and a profile face classifier is used to detect the multi-angle face.An improved horizontal differential projection algorithm is put forward to remove those non-face images among the preliminary detection results from the improved Adaboost algorithm.Experiment results show that compared with the classical Adaboost algorithm with a frontal face classifier,the textual DP-Adaboost algorithm can reduce false rate significantly and improve hit rate in multi-angle face detection.