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ISNet: Towards Improving Separability for Remote Sensing Image Change Detection
IEEE Transactions on Geoscience and Remote Sensing, 2022Deep learning has substantially pushed forward remote sensing image change detection through extracting discriminative hierarchical features. However, as the increasingly high-resolution remote sensing images have abundant spatial details but limited ...
Gong Cheng, Guangxing Wang, Jun-Wei Han
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Fast and Robust Attribute Reduction Based on the Separability in Fuzzy Decision Systems
IEEE Transactions on Cybernetics, 2021Attribute reduction is one of the most important preprocessing steps in machine learning and data mining. As a key step of attribute reduction, attribute evaluation directly affects classification performance, search time, and stopping criterion.
Meng Hu +3 more
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Categorization Training Increases the Perceptual Separability of Novel Dimensions
Cognition, 2015Fabian A. Soto Caro, Greg Ashby
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IEEE Transactions on Geoscience and Remote Sensing, 2021
Hyperspectral images (HSIs) have unique advantages in distinguishing subtle spectral differences of different materials. However, due to complex and diverse backgrounds, unknown prior knowledge, and imbalanced samples, it is challenging to separate ...
Jiaping Zhong +4 more
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Hyperspectral images (HSIs) have unique advantages in distinguishing subtle spectral differences of different materials. However, due to complex and diverse backgrounds, unknown prior knowledge, and imbalanced samples, it is challenging to separate ...
Jiaping Zhong +4 more
semanticscholar +1 more source
Measuring the Separability of Shape, Size, and Color in Scatterplots
International Conference on Human Factors in Computing Systems, 2019Scatterplots commonly use multiple visual channels to encode multivariate datasets. Such visualizations often use size, shape, and color as these dimensions are considered separable--dimensions represented by one channel do not significantly interfere ...
Stephen Smart, D. Szafir
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Separability and Compactness Network for Image Recognition and Superresolution
IEEE Transactions on Neural Networks and Learning Systems, 2019Convolutional neural networks (CNNs) have wide applications in pattern recognition and image processing. Despite recent advances, much remains to be done for CNNs to learn a better representation of image samples. Therefore, constant optimizations should
Li-Guo Zhou +3 more
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SIAM Journal on Discrete Mathematics, 1994
A separator in a graph \(G\) is a partition \((A,B,C)\) of \(V(G)\) such that \(| A|\), \(| B|\leq {2\over 3}| V(G)|\) and no vertex in \(A\) is adjacent to any vertex in \(B\); its order is \(| C|\). The authors give a short proof of a theorem of Lipton and Tarjan that for any planar graph with \(n\) vertices there is a separator of order \(\leq 2 ...
Noga Alon +2 more
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A separator in a graph \(G\) is a partition \((A,B,C)\) of \(V(G)\) such that \(| A|\), \(| B|\leq {2\over 3}| V(G)|\) and no vertex in \(A\) is adjacent to any vertex in \(B\); its order is \(| C|\). The authors give a short proof of a theorem of Lipton and Tarjan that for any planar graph with \(n\) vertices there is a separator of order \(\leq 2 ...
Noga Alon +2 more
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Order, 2019
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Nathan J. Bowler, Jakob Kneip
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zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Nathan J. Bowler, Jakob Kneip
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Communications of the ACM, 2012
Rsearchers now have the capability to look at the small-world problem from both the traditional algorithmic approach and the new topological approach.
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Rsearchers now have the capability to look at the small-world problem from both the traditional algorithmic approach and the new topological approach.
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Separating Einstein's separability
Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics, 2020zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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