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Table 4 Improvement in the precision performances of the object detection task for the vandalism detection system, thanks to the de nition of new control criteria.

in Real-Time Control of Video Surveillance Systems with Program Supervision Techniques
by B. Georis, F. Brémond, M. Thonnat 2006
Cited by 1

Table 4. Improvement of SCL and SCP recognition

in Single Character Chinese Named Entity Recognition
by Xiaodan Zhu Mu, Mu Li, Jianfeng Gao, Chang-ning Huang
"... In PAGE 5: ...2. The results in Table4 show that obvious improvement can be achieved on SCL and SCP after adapting source-channel models for SCNE. As shown in Table 5, the improvement of SCL and SCP has significant impact on performance of LN and PN 4 http://www.... ..."

Table 4. Improvement of SCL and SCP recognition

in unknown title
by unknown authors
"... In PAGE 5: ...2. The results in Table4 show that obvious improvement can be achieved on SCL and SCP after adapting source-channel models for SCNE. As shown in Table 5, the improvement of SCL and SCP has significant impact on performance of LN and PN 4 http://www.... ..."

Table 4. Improvement of SCL and SCP recognition

in Single Character Chinese Named Entity Recognition
by Xiaodan Zhu Mu, Mu Li, Jianfeng Gao, Chang-ning Huang
"... In PAGE 5: ...2. The results in Table4 show that obvious improvement can be achieved on SCL and SCP after adapting source-channel models for SCNE. As shown in Table 5, the improvement of SCL and SCP has significant impact on performance of LN and PN 4 http://www.... ..."

Table 2 Comparison of car detection results on test set A Method No. of correct detections No. of false detections

in + model ARTICLE IN PRESS Abstract
by Hongming Zhang A, Wen Gao A, Xilin Chen B, Debin Zhao A 2005
"... In PAGE 9: ... As the fine object detection method, the SVM classification improves the detection precisions without significant loss of detection rates. In Table2 and Table 3, the experimental results on test sets A and B are compared with the results reported on the same data sets from Agrawal et al. [15].... ..."

Table 1. Parameters Used in the Models of the Stick-Pulling Experiment Mean Mean Wall Mean Seed Mean Robot

in Downloaded from
by Alcherio Martinoli, Kjerstin Easton, William Agassounon, Alcherio Martinoli, Kjerstin Easton, William Agassounon
"... In PAGE 10: ...ig. 3. A simple subchain consisting of a search and an obstacle avoidance state. The numerical values used in this example have been derived from the values of Table1 and Table 2 using parameters for a generic obstacle: Ta = 2 iterations and pa is a function of the setup (for example, pa = 0.63 for the mean probability of encountering an obstacle in an arena of 40 cm, four robots, and four sticks; in this case teammates, walls, and sticks are considered all as obstacles).... ..."

Table 3 Comparison of car detection results on test set B Method No. of correct detections No. of false

in + model ARTICLE IN PRESS Abstract
by Hongming Zhang A, Wen Gao A, Xilin Chen B, Debin Zhao A 2005
"... In PAGE 9: ... As the fine object detection method, the SVM classification improves the detection precisions without significant loss of detection rates. In Table 2 and Table3 , the experimental results on test sets A and B are compared with the results reported on the same data sets from Agrawal et al. [15].... ..."

Table 6 Comparison of text detection results on the video text set

in + model ARTICLE IN PRESS Abstract
by Hongming Zhang A, Wen Gao A, Xilin Chen B, Debin Zhao A 2005
"... In PAGE 13: ... In the fine object detection stage, the SVM improves detection precisions without significant loss of detection rates. In Table6 , the experimental results on the video text detection test set are compared with the results reported on the same date set from Hua et al. [44].... ..."

Table I: Improvement in damage detectability

in unknown title
by unknown authors

Table I. Object Detection Categories

in Object Tracking: A Survey
by Alper Yilmaz, Omar Javed, Mubarak Shah 2001
Cited by 4
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