Visual semantic alignment network based on pre-trained ViT for few-shot image classification

Jiaming Zhang; Jijie Wu; Xiaoxu Li

doi:10.1109/apsipaasc63619.2025.10849256

ScienceGate Book Chapters

JOURNAL ARTICLE

Visual semantic alignment network based on pre-trained ViT for few-shot image classification

Jiaming Zhang Jijie Wu Xiaoxu Li

Year: 2024 Pages: 1-6

DOI: 10.1109/apsipaasc63619.2025.10849256

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Artificial intelligence Shot (pellet) Contextual image classification Image (mathematics) Computer vision Pattern recognition (psychology) Chemistry

Metrics

Cited By

0.00

FWCI (Field Weighted Citation Impact)

Refs

0.41

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Topics

Image Processing Techniques and Applications

Physical Sciences → Engineering → Media Technology

Advanced Vision and Imaging

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Video Analysis and Summarization

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Visual semantic alignment network based on pre-trained ViT for few-shot image classification

Metrics

Topics

Related Documents

Local feature semantic alignment network for few-shot image classification

KLSANet: Key local semantic alignment Network for few-shot image classification

VPPT: Visual Pre-Trained Prompt Tuning Framework for Few-Shot Image Classification

Multi-branch semantic alignment for few-shot image classification

PRSN: Prototype resynthesis network with cross-image semantic alignment for few-shot image classification