LN-DETR: An efficient Transformer architecture for lung nodule detection with multi-scale feature fusion

Jialiang Tang; Xiao Chen; Linyuan Fan; Zhihui Zhu; Chen Huang

doi:10.1016/j.neucom.2025.129827

ScienceGate Book Chapters

JOURNAL ARTICLE

LN-DETR: An efficient Transformer architecture for lung nodule detection with multi-scale feature fusion

Jialiang Tang Xiao Chen Linyuan Fan Zhihui Zhu Chen Huang

Year: 2025 Journal: Neurocomputing Vol: 633 Pages: 129827-129827 Publisher: Elsevier BV

DOI: 10.1016/j.neucom.2025.129827

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Architecture Artificial intelligence Pattern recognition (psychology) Transformer Fusion Scale (ratio) Feature (linguistics) Cartography Engineering Geography Electrical engineering

Metrics

Cited By

68.46

FWCI (Field Weighted Citation Impact)

Refs

1.00

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Lung Cancer Diagnosis and Treatment

Health Sciences → Medicine → Pulmonary and Respiratory Medicine

Advanced Chemical Sensor Technologies

Physical Sciences → Engineering → Biomedical Engineering

LN-DETR: An efficient Transformer architecture for lung nodule detection with multi-scale feature fusion

Metrics

Citation History

Topics

Related Documents

LN-DETR: cross-scale feature fusion and re-weighting for lung nodule detection

MSA-DETR: multi-scale alignment detection transformer for PCB defect detection with enhanced cross-scale feature fusion

MAF-DETR: Defect Detection with Multi-Scale Adaptive Feature Fusion

IR-DETR: An efficient detection transformer with multi-layer feature fusion for infrared small targets

HybridScale-GuideTokens DETR: Enhancing Object Detection with GuideToken-Optimized Multi-scale Feature Fusion in a Transformer Model