Semantic change of robust
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DOI: 10.1017/s0266078424000257
Abstract: Abstract This paper aims to demonstrate that robust is currently undergoing a semantic shift, transforming itself into a quasi-intensifier of nouns, conveying positive evaluative meanings. The etymology and semantic development of robust is traced using… read more here.
Keywords: language; semantic change; change robust;
A state-of-the-art of semantic change computation
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DOI: 10.1017/s1351324918000220
Abstract: Abstract This paper reviews the state-of-the-art of one emergent field in computational linguistics—semantic change computation. It summarizes the literature by proposing a framework that identifies five components in the field: diachronic corpus, diachronic word sense… read more here.
Keywords: change computation; semantic change; change; state art ... See more keywords
Multitask semantic change detection guided by spatiotemporal semantic interaction
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DOI: 10.1038/s41598-025-00750-8
Abstract: Semantic Change Detection (SCD) aims to accurately identify the change areas and their categories in dual-time images, which is more complex and challenging than traditional binary change detection tasks. Accurately capturing the change information of… read more here.
Keywords: detection; change detection; multitask semantic; semantic change ... See more keywords
A transformer-based Siamese network and an open optical dataset for semantic change detection of remote sensing images
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Digital Earth"
DOI: 10.1080/17538947.2022.2111470
Abstract: ABSTRACT Recent change detection (CD) methods focus on the extraction of deep change semantic features. However, existing methods overlook the fine-grained features and have the poor ability to capture long-range space–time information, which leads to… read more here.
Keywords: change detection; change; semantic change; transformer based ... See more keywords
SFSCDNet: A Deep Learning Model With Spatial Flow-Based Semantic Change Detection From Bi-Temporal Satellite Images
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DOI: 10.1109/access.2024.3520428
Abstract: Semantic change detection in remote sensing imagery plays a pivotal role in urban planning, environmental monitoring, and disaster assessment applications. Existing deep learning-based methods, particularly those relying on triple-branch architectures, often struggle to accurately localize… read more here.
Keywords: deep learning; change detection; semantic change; network ... See more keywords
Spatially and Semantically Enhanced Siamese Network for Semantic Change Detection in High-Resolution Remote Sensing Images
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2022.3159528
Abstract: Given a pair of bitemporal very high resolution (VHR) remote sensing images, the semantic change detection task aims to locate land surface changes and identify their semantic classes. The existing algorithms use independent branches to… read more here.
Keywords: change detection; remote sensing; change; semantically enhanced ... See more keywords
Adaptive Self-Paced Collaborative and 3-D Adversarial Multitask Network for Semantic Change Detection Using Zhuhai-1 Orbita Hyperspectral Remote Sensing Imagery
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.2023.3348572
Abstract: In recent years, numerous change detection methodologies have been proposed, with a predominant focus on binary change detection. Furthermore, there exists a paucity of research addressing semantic change detection in scenarios where solely binary change… read more here.
Keywords: multitask network; semantic change; change detection; change ... See more keywords
SSTNet: A Network Based on Modeling of Semantic-Spatiotemporal Information for Semantic Change Detection of 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.2024.3464117
Abstract: Semantic change detection (SCD) aiming to localize changes and identify their types is a complex pixel-level classification task. In SCD, detecting changes of narrow and long objects (NLOs) common in various scenarios is more challenging… read more here.
Keywords: information; change detection; semantic change; change ... See more keywords
Deep-Learning-Based Semantic Change Detection for Urban Greenery and Comprehensive Urban Areas
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DOI: 10.1109/jstars.2024.3511597
Abstract: Urban greenery is important for maintaining ecological balance and enhancing urban ecosystems. However, it is significantly degrading due to human activities and natural disasters, making it essential to monitor both urban greenery and the overall… read more here.
Keywords: urban greenery; semantic change; greenery; change detection ... See more keywords
Multitask Change-Aware Network and Semisupervised Enhanced Multistep Training for Semantic Change Detection
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2025.3554272
Abstract: Semantic change detection (SCD) aims to find out where and what changes between a pair of co-registered remote sensing images. Compared to binary change detection, which only predicts the location of changes, SCD provides detailed… read more here.
Keywords: change detection; remote sensing; multitask change; semantic change ... See more keywords
SChanger: Change Detection From a Semantic Change and Spatial Consistency Perspective
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2025.3555849
Abstract: Change detection is a key task in Earth observation applications. Recently, deep learning methods have demonstrated strong performance and widespread application. However, change detection faces data scarcity due to the labor-intensive process of accurately aligning… read more here.
Keywords: spatial consistency; semantic change; change detection; change ... See more keywords