Work

IDNet: Intensity-Constrained Detail-Enhanced Network for Hyperspectral and LiDAR Collaborative Classification

Year: 2025

Type: article

Source: IEEE Transactions on Geoscience and Remote Sensing

DOI: 10.1109/tgrs.2025.3589143

Authors: Chao Liang, Yuqing Zhao, Yu Song, Kang Ni

Institutions: Changchun University of Technology, Nanjing University of Posts and Telecommunications

Language: English

Topic: Remote-Sensing Image Classification

Subfield: Media Technology

Field: Engineering

Domain: Physical Sciences

Open Access status: closed

Funders: National Natural Science Foundation of China, China Postdoctoral Science Foundation, Science and Technology Program of Zhejiang Province

Awards: G1480591243, G4106820521, G5409677342

OpenAlex ID: W4412404183

FWCI: 4.3

Cites: 52

Cited by: 10

Related to: 10