EMNet: A Novel Few-Shot Image Classification Model with Enhanced Self-Correlation Attention and Multi-Branch Joint Module
In this research, inspired by the principles of biological visual attention mechanisms and swarm intelligence found in nature, we present an Enhanced Self-Correlation Attention and Multi-Branch Joint Module Network (EMNet), a novel model for few-shot image classification. Few-shot image classificati...
Saved in:
Main Authors: | Fufang Li, Weixiang Zhang, Yi Shang |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-01-01
|
Series: | Biomimetics |
Subjects: | |
Online Access: | https://www.mdpi.com/2313-7673/10/1/16 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Few-Shot Knowledge Graph Completion Model With Neighbor Filter and Affine Attention
by: Hongfang Gong, et al.
Published: (2025-01-01) -
Attention-enhanced corn disease diagnosis using few-shot learning and VGG16
by: Ruchi Rani, et al.
Published: (2025-06-01) -
Contrastive meta-learning framework for few-shot cross-lingual text classification
by: GUO Jianming, et al.
Published: (2024-06-01) -
A network intrusion detection method designed for few-shot scenarios
by: Weichen HU, et al.
Published: (2023-10-01) -
MSO‐DETR: Metric space optimization for few‐shot object detection
by: Haifeng Sima, et al.
Published: (2024-12-01)