EPANet-KD: Efficient progressive attention network for fine-grained provincial village classification via knowledge distillation.

ABSTRACT:

Objective

Fine-grained classification of historical traditional villages plays a crucial role in guiding the future development and construction of urban and rural areas. This study aims to propose a new dataset for fine-grained classification of traditional villages and to propose an efficient progressive attention network for the problem of low accuracy and efficiency of fine-grained traditional historical village classification.

Methods and results

Firstly, in order to further study the long-standing problem of fine-grained classification of traditional villages, a new fine-grained classification dataset of traditional villages containing 4,400 images, referred to as PVCD, is proposed by crawling and hand-arranging. Secondly, a new Progressive Attention Module, abbreviate

SUBMITTER: Zhang C 

PROVIDER: S-EPMC10868776 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature