Prototype-Aligned Federated Learning for Robust Object Extraction in Heterogeneous Remote Sensing
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2025.3587683
Abstract: Federated learning (FL) has emerged as a pivotal collaborative machine learning framework, enabling privacy-preserving analytics for smart city applications using distributed data from Internet of Things (IoT) devices. However, the inherent data heterogeneity that arises… read more here.
Keywords: extraction heterogeneous; prototype; heterogeneous remote; remote sensing ... See more keywords
An Enhanced and Unsupervised Siamese Network With Superpixel-Guided Learning for Change Detection in Heterogeneous Remote Sensing Images
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2024.3479703
Abstract: In this article, we consider the issue of change detection (CD) for heterogeneous remote sensing images. Existing deep learning-based methods for CD usually utilize square convolution receptive fields, which do not sufficiently exploit the contextual… read more here.
Keywords: change detection; heterogeneous remote; remote sensing; superpixel ... See more keywords
Bipartite Adversarial Autoencoders With Structural Self-Similarity for Unsupervised Heterogeneous Remote Sensing Image Change Detection
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2022.3201925
Abstract: Images from different sensors can be different in intensity or data structure to present the same object on the ground. The distinct appearances make the change detection task more difficult to obtain accurate change regions.… read more here.
Keywords: change detection; heterogeneous remote; remote sensing; image ... See more keywords