2016
DOI: 10.20965/jaciii.2016.p0041
|View full text |Cite
|
Sign up to set email alerts
|

Improved Object Recognition with Decision Trees Using Subspace Clustering

Abstract: Generic object recognition algorithms usually require complex classificationmodels because of intrinsic difficulties arising from problems such as changes in pose, lighting conditions, or partial occlusions. Decision trees present an inexpensive alternative for classification tasks and offer the advantage of being simple to understand. On the other hand, a common scheme for object recognition is given by the appearances of visual words, also known as the bag-of-words method. Although multiple co-occurrences of… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Year Published

2019
2019
2019
2019

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
references
References 17 publications
0
0
0
Order By: Relevance