CNN and Transformer Encoder Performance Analysis Based on Few-Shot Learning for Road Damage Classification > Domestic Conference Papers | 한국교통대학교 AMI Lab.

Publication

Algorithmic Machine Intelligence Laboratory.

2025 CNN and Transformer Encoder Performance Analysis Based on Few-Shot Learning for Road Damage Classification

페이지 정보

작성자 최고관리자 작성일 26-04-08 15:27

본문

Authors: Jaehyun Lee, Changjoon Park, Namjung Kim, Junhwi Park, Xufeng Hu, Jeonghwan Gawk

Conference: Korea Society of Computer Information

Location / Date: 제주대학교 아라캠퍼스 / July 11

Year: 2025

목록

이전글Comparative Analysis of Pothole Anomaly Detection Performance Using CNN and Transformer Based Feature Extractors in MSFlow
다음글A Multi-Task Learning Approach for Pothole and Crack Classification Using Vision Transformers