Semantic automatic image annotation based on Non-Abstract Visual Keywords

2015 ◽  
pp. 243-248
Author(s):  
Xiao Ke ◽  
Guolong Chen
Keyword(s):  
Image Annotation ◽  
Automatic Image Annotation ◽  
Visual Keywords

Context Dependent Automatic Textile Image Annotation Using Networked Knowledge

2007 ◽  
Vol 11 (6) ◽  
pp. 633-640
Author(s):  
Yosuke Furukawa ◽  
◽  
Yusuke Kamoi ◽  
Tatsuya Sato ◽  
Tomohiro Takagi
Keyword(s):  
Image Annotation ◽  
Image Features ◽  
New Method ◽  
Automatic Image Annotation ◽  
Annotation System ◽  
Specialist Knowledge ◽  
Feature Values ◽  
High Level ◽  
Improved Accuracy ◽  
Visual Keywords

This paper presents a new method of an automatic image annotation system that estimates keywords from an image. Typical automatic image annotation systems extract features from an image and recognize keywords. However this method has two problems. One is that it treats features statically. Features should change depending on what keywords are attached so keywords should not be treated equally. Another is that it does not consider the level of keywords. Visual keywords, such as color or texture, can be recognized easily from image features, while high-level semantics such as context are hard to recognize from the features. To solve these problems, our approach is to recognize context by using networked specialist knowledge and to recognize keywords by changing feature values dynamically depending on the context. To evaluate our system, we conducted two experiments of applying it to textile images. As a result, we obtained improved accuracy and confirmed the effectiveness of using networked knowledge.

Multi-class particle swarm model selection for automatic image annotation

2012 ◽  
Vol 39 (12) ◽  
pp. 11011-11021 ◽  
Author(s):  
Hugo Jair Escalante ◽  
Manuel Montes ◽  
L. Enrique Sucar
Keyword(s):  
Model Selection ◽  
Image Annotation ◽  
Particle Swarm ◽  
Automatic Image Annotation ◽  
Selection For

scholarly journals Automatic image annotation based on deep learning models: a systematic review and future challenges

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Myasar Mundher Adnan ◽  
Mohd Shafry Mohd Rahim ◽  
Amjad Rehman ◽  
Zahid Mehmood ◽  
Tanzila Saba ◽  
...  
Keyword(s):  
Systematic Review ◽  
Deep Learning ◽  
Image Annotation ◽  
Automatic Image Annotation ◽  
Learning Models ◽  
Future Challenges
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