Deep learning for construction waste detection using ConvNeXt V2 EMA attention and WIoU v3 loss

D Dong Han (National Synchrotron Radiation Laboratory) M Ming Ma (State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, 38 Xueyuan Road, Haidian District, Beijing 100191, China) X Xiao Li J Jin Zhu C Chunyu Zhao (Gladstone Institute of Data Science and Biotechnology) L Liang Yu (State Key Laboratory of Catalysis) Y Ying Tian J Jingnan Chen (State Key Laboratory of Natural and Biomimetic Drugs, Chemical Biology Center, and Department of Chemical Biology at School of Pharmaceutical Sciences)

Article Details

Volume / Issue Vol. 16, Issue 1
Published January 28, 2026
ISSN 2045-2322
Publisher Nature Portfolio

Journal Info

Scientific Reports

Nature Portfolio

ISSN: 2045-2322 Open Access Life Sciences

Authors (8)

D

Dong Han

National Synchrotron Radiation Laboratory

M

Ming Ma

State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, 38 Xueyuan Road, Haidian District, Beijing 100191, China

X

Xiao Li

J

Jin Zhu

C

Chunyu Zhao

Gladstone Institute of Data Science and Biotechnology

L

Liang Yu

State Key Laboratory of Catalysis

Y

Ying Tian

J

Jingnan Chen

State Key Laboratory of Natural and Biomimetic Drugs, Chemical Biology Center, and Department of Chemical Biology at School of Pharmaceutical Sciences