A Self-Supervised Learning Method for Shadow Detection in Remote Sensing Imagery

Shoulin Yin; Jie Liu; Hang Li

doi:10.1007/s13319-018-0204-9

ScienceGate Book Chapters

JOURNAL ARTICLE

A Self-Supervised Learning Method for Shadow Detection in Remote Sensing Imagery

Shoulin Yin Jie Liu Hang Li

Year: 2018 Journal: 3D Research Vol: 9 (4) Publisher: Springer Science+Business Media

DOI: 10.1007/s13319-018-0204-9

Get Full-Text PDF Get Analytical Report

Keywords:

Shadow (psychology) Computer science Artificial intelligence Histogram Computer vision Feature (linguistics) Object detection Pattern recognition (psychology) Image (mathematics)

Metrics

Cited By

1.59

FWCI (Field Weighted Citation Impact)

Refs

0.84

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Video Surveillance and Tracking Methods

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Fire Detection and Safety Systems

Physical Sciences → Engineering → Safety, Risk, Reliability and Quality

Remote-Sensing Image Classification

Physical Sciences → Engineering → Media Technology

A Self-Supervised Learning Method for Shadow Detection in Remote Sensing Imagery

Metrics

Citation History

Topics

Related Documents

SACNet: A Novel Self-Supervised Learning Method for Shadow Detection from High-Resolution Remote Sensing Images

Self-supervised multimodal change detection based on difference contrast learning for remote sensing imagery

Semi-Supervised Cloud Detection for Remote Sensing Imagery via Self-Training

Domain Adaptable Self-supervised Representation Learning on Remote Sensing Satellite Imagery

A Weakly-Supervised, Multitask Deep Learning Framework for Shadow Mitigation in Remote Sensing Imagery