Learning deep semantic segmentation network under multiple weakly-supervised constraints for cross-domain remote sensing image semantic segmentation
Due to its wide applications, remote sensing (RS) image semantic segmentation has
attracted increasing research interest in recent years. Benefiting from its hierarchical abstract …
attracted increasing research interest in recent years. Benefiting from its hierarchical abstract …
Domain adaptation from daytime to nighttime: A situation-sensitive vehicle detection and traffic flow parameter estimation framework
Vehicle detection in traffic surveillance images is an important approach to obtain vehicle
data and rich traffic flow parameters. Recently, deep learning based methods have been …
data and rich traffic flow parameters. Recently, deep learning based methods have been …
Convolutional neural networks based remote sensing scene classification under clear and cloudy environments
Remote sensing (RS) scene classification has wide applications in the environmental
monitoring and geological survey. In the real-world applications, the RS scene images taken …
monitoring and geological survey. In the real-world applications, the RS scene images taken …
An unsupervised domain adaptation approach for change detection and its application to deforestation mapping in tropical biomes
PJS Vega, GAOP da Costa, RQ Feitosa… - ISPRS Journal of …, 2021 - Elsevier
Abstract Changes in environmental conditions, geographical variability and different sensor
properties typically make it almost impossible to employ previously trained classifiers for …
properties typically make it almost impossible to employ previously trained classifiers for …
Mapping and analyzing the local climate zones in China's 32 major cities using Landsat imagery based on a novel convolutional neural network
ABSTRACT The Local Climate Zone (LCZ) scheme provides researchers with a standard
method to monitor the Urban Heat Island (UHI) effect and conduct temperature studies. How …
method to monitor the Urban Heat Island (UHI) effect and conduct temperature studies. How …
Remote sensing scene classification using sparse representation-based framework with deep feature fusion
S Mei, K Yan, M Ma, X Chen… - IEEE Journal of …, 2021 - ieeexplore.ieee.org
Scene classification of high-resolution remote sensing (RS) images has attracted increasing
attentions due to its vital role in a wide range of applications. Convolutional neural networks …
attentions due to its vital role in a wide range of applications. Convolutional neural networks …
An open set domain adaptation algorithm via exploring transferability and discriminability for remote sensing image scene classification
Remote sensing image scene classification aims to automatically assign semantic labels for
remote sensing images. Recently, to overcome the distribution discrepancy of training data …
remote sensing images. Recently, to overcome the distribution discrepancy of training data …
Unsupervised adversarial domain adaptation with error-correcting boundaries and feature adaption metric for remote-sensing scene classification
C Ma, D Sha, X Mu - Remote Sensing, 2021 - mdpi.com
Unsupervised domain adaptation (UDA) based on adversarial learning for remote-sensing
scene classification has become a research hotspot because of the need to alleviating the …
scene classification has become a research hotspot because of the need to alleviating the …
Fusing deep features by kernel collaborative representation for remote sensing scene classification
X Chen, M Ma, Y Li, W Cheng - IEEE Journal of Selected Topics …, 2021 - ieeexplore.ieee.org
Remote sensing scene classification is widely concerned because of its wide applications.
Recently, convolutional neural networks (CNNs) have made a significant breakthrough in …
Recently, convolutional neural networks (CNNs) have made a significant breakthrough in …
Learning to detect phone-related pedestrian distracted behaviors with synthetic data
Due to the popularity and mobility of smart phones, phone-related pedestrian distracted
behaviors, eg, Texting, Game Playing, and Phone calls, have caused many traffic fatalities …
behaviors, eg, Texting, Game Playing, and Phone calls, have caused many traffic fatalities …