Summary of fine-grained image recognition based on attention mechanism

Yao Ma; Min Zhi

doi:10.1117/12.2623383

16 February 2022 Summary of fine-grained image recognition based on attention mechanism

Yao Ma, Min Zhi

Proceedings Volume 12083, Thirteenth International Conference on Graphics and Image Processing (ICGIP 2021); 120832J (2022) https://doi.org/10.1117/12.2623383
Event: Thirteenth International Conference on Graphics and Image Processing (ICGIP 2021), 2021, Kunming, China

Abstract

Attention mechanism is one of the most basic and core tasks in computer vision. Its essence is to locate the information in the region of interest and suppress useless information. The results are usually displayed in the form of probability graph or probability eigenvector. Attention mechanism has become an important concept in convolutional neural network, which has been widely studied in different application fields and has strong practical value. This paper introduces the classification of attention mechanism and its application in fine-grained image recognition. The classification is mainly divided into channel attention mechanism, spatial attention mechanism and channel spatial mixed attention mechanism. Finally, the future research direction of attention mechanism in fine-grained images is discussed.

Citation Download Citation

Yao Ma and Min Zhi "Summary of fine-grained image recognition based on attention mechanism", Proc. SPIE 12083, Thirteenth International Conference on Graphics and Image Processing (ICGIP 2021), 120832J (16 February 2022); https://doi.org/10.1117/12.2623383

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
7 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Neural networks

Convolution

Image classification

Convolutional neural networks

Feature extraction

Image processing

Visualization

Show All Keywords

Keywords/Phrases

Search In:

Publication Years