Results 21 to 30 of about 323,408 (293)
Change Alignment-Based Image Transformation for Unsupervised Heterogeneous Change Detection
Remote Sensing, 2022 Change detection (CD) with heterogeneous images is currently attracting extensive attention in remote sensing. In order to make heterogeneous images comparable, the image transformation methods transform one image into the domain of another image, which ...
Kuowei Xiao, Yuli Sun, Lin Lei
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Self-Collaborative Unsupervised Hashing for Large-Scale Image Retrieval
IEEE Access, 2022 Learning based hashing approaches have achieved considerable success in large-scale image retrieval due to the query effectiveness and efficiency. However, most studies highly rely on supervised knowledge like data labels, thus might fail in unsupervised
Hongmin Zhao, Zhigang Luo
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Unsupervised Volumetric Animation
2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023 We propose a novel approach for unsupervised 3D animation of non-rigid deformable objects. Our method learns the 3D structure and dynamics of objects solely from single-view RGB videos, and can decompose them into semantically meaningful parts that can be tracked and animated.
CHAI MENGLEI +7 more
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Evaluating Unsupervised Denoising Requires Unsupervised Metrics
CoRR, 2022 Unsupervised denoising is a crucial challenge in real-world imaging applications. Unsupervised deep-learning methods have demonstrated impressive performance on benchmarks based on synthetic noise. However, no metrics are available to evaluate these methods in an unsupervised fashion. This is highly problematic for the many practical applications where
Adria Marcos-Morales +7 more
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A Survey on Semi-, Self- and Unsupervised Learning for Image Classification
IEEE Access, 2021 While deep learning strategies achieve outstanding results in computer vision tasks, one issue remains: The current strategies rely heavily on a huge amount of labeled data.
Lars Schmarje +3 more
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Unsupervised Few-Shot Feature Learning via Self-Supervised Training
Frontiers in Computational Neuroscience, 2020 Learning from limited exemplars (few-shot learning) is a fundamental, unsolved problem that has been laboriously explored in the machine learning community.
Zilong Ji +4 more
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A Visualization Framework for Unsupervised Analysis of Latent Structures in SAR Image Time Series
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 Openly available satellite image time series (SITS) are considered an important resource for spatiotemporal change monitoring. However, obtaining semantically annotated datasets for such tasks is an expensive affair.
Chandrabali Karmakar +3 more
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IEEE Access, 2020 Unsupervised anomaly detection for spatio-temporal data has extensive use in a wide variety of applications such as earth science, traffic monitoring, fraud and disease outbreak detection.
Yildiz Karadayi +2 more
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Video Object Segmentation by Latent Outcome Regression
IEEE Access, 2020 This paper presents a novel algorithm for unsupervised video object segmentation (UVOS) in unconstrained scenarios. Although a large variety of methods have been proposed in the literature, segmenting generic objects is still challenging because ...
Lin Zhang, Yao Lu
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Over-the-Counter Use of Medical Abortion Pills: A Prospective Cohort Study [PDF]
Journal of Clinical and Diagnostic Research, 2023 Introduction: Medical abortion is a safe intervention in the first trimester that requires access to accurate information and the support of a trained healthcare provider.
Reema Kumari +2 more
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