Results 11 to 20 of about 33,441 (257)
Semantic Change Detection With Gaussian Word Embeddings [PDF]
IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2021 Diachronic study of the evolution of languages is of importance in natural language processing (NLP). Recent years have witnessed a surge of computational approaches for the detection and characterization of lexical semantic change (LSC) due to the availability of diachronic corpora and advancing word representation techniques.
Arda Yuksel, Berke Ugurlu, Aykut Koc
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Scalable and Interpretable Semantic Change Detection [PDF]
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021 Several cluster-based methods for semantic change detection with contextual embeddings emerged recently. They allow a fine-grained analysis of word use change by aggregating embeddings into clusters that reflect the different usages of the word. However, these methods are unscalable in terms of memory consumption and computation time.
Montariol, Syrielle +2 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 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.
Manqi Zhao +6 more
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Remote Sensing, 2023 High-resolution remote sensing image change detection technology compares and analyzes bi-temporal or multitemporal high-resolution remote sensing images to determine the change areas.
Shiyan Pang +4 more
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SiameseNet Based Fine-Grained Semantic Change Detection for High Resolution Remote Sensing Images
Remote Sensing, 2023 Change detection in high resolution (HR) remote sensing images faces more challenges than in low resolution images because of the variations of land features, which prompts this research on faster and more accurate change detection methods.
Lili Zhang +5 more
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Semantic supported urban change detection using ALS point clouds
International Journal of Applied Earth Observations and Geoinformation, 2023 Airborne laser scanning (ALS) has experienced significant development and boosted widespread applications over the recent years. With increasing data quality and acquisition convenience, multi-temporal ALS point clouds have been used for change detection
Li Fang +4 more
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Beyond Classifiers: Remote Sensing Change Detection with Metric Learning
Remote Sensing, 2022 For change detection in remote sensing images, supervised learning always relies on bi-temporal images as inputs and 2-class/multi-class classifiers as outputs. On the other hand, change detection can be viewed as a metric learning problem, i.e., changed
Yuqi Zhang +4 more
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Ecological Indicators, 2023 The utility of semantic change detection in myriad change scenarios has garnered considerable attention in contemporary research; however, its applicability in monitoring alterations in wetland ecosystems remains incompletely elucidated.
Yulin Pan +6 more
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Leida xuebao, 2014 This paper discusses the change detection in high-resolution SAR image interpretation. Referring to the unfavorable elements in the change detection and the status quo, this paper focuses on resolving the semantic information deficiency problem in SAR ...
Fu Yao-yao +3 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 Change detection based on remote sensing data is an important method to detect the earth surface changes. With the development of deep learning, convolutional neural networks have excelled in the field of change detection.
Xintao Xu, Jinjiang Li, Zheng Chen
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