Keyword : Random Forest


Vision Based Nighttime Vehicle Detection Using Adaptive Threshold and Multi-Class Classification
Yuta SAKAGAWA Kosuke NAKAJIMA Gosuke OHASHI 
Publication:   
Publication Date: 2019/09/01
Vol. E102-A  No. 9 ; pp. 1235-1245
Type of Manuscript:  Special Section PAPER (Special Section on Image Media Quality)
Category: 
Keyword: 
intelligent transportation systemsnighttime driving scenesvehicle detectionNiblack thresholdingRandom Forestmathematical morphology
 Summary | Full Text:PDF(3.1MB)

Boosted Random Forest
Yohei MISHINA Ryuei MURATA Yuji YAMAUCHI Takayoshi YAMASHITA Hironobu FUJIYOSHI 
Publication:   IEICE TRANSACTIONS on Information and Systems
Publication Date: 2015/09/01
Vol. E98-D  No. 9 ; pp. 1630-1636
Type of Manuscript:  Special Section PAPER (Special Section on Optimization and Learning Algorithms of Small Embedded Devices and Related Software/Hardware Implementation)
Category: 
Keyword: 
BoostingRandom Forestmachine learningpattern recognition
 Summary | Full Text:PDF(744.9KB)

Improving Hough Based Pedestrian Detection Accuracy by Using Segmentation and Pose Subspaces
Jarich VANSTEENBERGE Masayuki MUKUNOKI Michihiko MINOH 
Publication:   IEICE TRANSACTIONS on Information and Systems
Publication Date: 2014/10/01
Vol. E97-D  No. 10 ; pp. 2760-2768
Type of Manuscript:  PAPER
Category: Image Recognition, Computer Vision
Keyword: 
Hough based detectionspedestrian segmentationpose estimationRandom ForestkPCA
 Summary | Full Text:PDF(1.9MB)