Fish image classification based on MobileNet

Ziming Miao; Han Liu; Guangming Xian; Junhong Xie

doi:10.1117/12.3026347

27 March 2024 Fish image classification based on MobileNet

Ziming Miao, Han Liu, Guangming Xian, Junhong Xie

Proceedings Volume 13105, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023); 1310511 (2024) https://doi.org/10.1117/12.3026347
Event: 3rd International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023), 2023, Qingdao, China

Abstract

Fine-grained image classification aims to accurately categorize subclasses within a particular category. Due to the small inter-class differences and large intra-class variations, fine-grained image classification has been a challenging research topic in the field of computer vision and holds significant research value. Existing neural network-based algorithms suffer from the loss of fine-grained texture details during the training process and the inability to effectively fuse features extracted from different convolution layers of the backbone network. To address these issues, this paper proposes a fine-grained image classification method based on a lightweight feature extraction network with MobileNet v2 as the core, incorporating multi-scale feature fusion and attention mechanism. Considering that high-level and low-level features contain rich semantic and textural information, attention mechanisms are embedded into different scales to capture more diverse feature information. Experimental evaluations conducted on the publicly available fine-grained dataset, A Large Scale Fish Dataset, achieve a classification accuracy of 99.86%. The results demonstrate the superiority of the proposed method in fine-grained object classification.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Ziming Miao, Han Liu, Guangming Xian, and Junhong Xie "Fish image classification based on MobileNet", Proc. SPIE 13105, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023), 1310511 (27 March 2024); https://doi.org/10.1117/12.3026347

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