Results 41 to 50 of about 16,712,425 (389)
Inferring causal relations from observational long-term carbon and water fluxes records
Scientific Reports, 2022 Land, atmosphere and climate interact constantly and at different spatial and temporal scales. In this paper we rely on causal discovery methods to infer spatial patterns of causal relations between several key variables of the carbon and water cycles ...
Emiliano Díaz +4 more
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IEEE Access, 2019 In this paper, a novel multilayer hidden conditional random fields (MHCRFs)-based cervical histopathology image classification (CHIC) model is proposed to classify well, moderate and poorly differentiation stages of cervical cancer using a weakly ...
Chen Li +7 more
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DoMars16k: A Diverse Dataset for Weakly Supervised Geomorphologic Analysis on Mars
Remote Sensing, 2020 Mapping planetary surfaces is an intricate task that forms the basis for many geologic, geomorphologic, and geographic studies of planetary bodies. In this work, we present a method to automate a specific type of planetary mapping, geomorphic mapping ...
Thorsten Wilhelm +6 more
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Feature Encoder Guided Generative Adversarial Network for Face Photo-Sketch Synthesis
IEEE Access, 2019 Face photo-sketch synthesis often suffers from many problems, such as low clarity, facial distortion, contents loss, texture missing and color inconsistency in the synthesized images.
Jieying Zheng +4 more
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Extended Global–Local Representation Learning for Video Person Re-Identification
IEEE Access, 2019 Recently, person re-identification has become one of the research hotspots in the field of computer vision and has received extensive attention in the academic community.
Wanru Song +4 more
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Applied Sciences, 2022 Currently, the field of transparent image analysis has gradually become a hot topic. However, traditional analysis methods are accompanied by large amounts of carbon emissions, and consumes significant manpower and material resources.
Hechen Yang +9 more
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A survey on Image Data Augmentation for Deep Learning
Journal of Big Data, 2019 Deep convolutional neural networks have performed remarkably well on many Computer Vision tasks. However, these networks are heavily reliant on big data to avoid overfitting. Overfitting refers to the phenomenon when a network learns a function with very
Connor Shorten, T. Khoshgoftaar
semanticscholar +1 more source
Deep Residual Learning for Image Recognition [PDF]
Computer Vision and Pattern Recognition, 2015 Deeper neural networks are more difficult to train. We present a residual learning framework to ease the training of networks that are substantially deeper than those used previously.
Kaiming He +3 more
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Taming Transformers for High-Resolution Image Synthesis [PDF]
Computer Vision and Pattern Recognition, 2020 Designed to learn long-range interactions on sequential data, transformers continue to show state-of-the-art results on a wide variety of tasks. In contrast to CNNs, they contain no inductive bias that prioritizes local interactions.
Patrick Esser, Robin Rombach, B. Ommer
semanticscholar +1 more source
Weighted Direct Nonlinear Regression for Effective Image Interpolation
IEEE Access, 2019 This paper proposes a learning-based image interpolation method based on weighted direct nonlinear regression. It attempts to learn the nonlinear relationship between the low-resolution patches and their corresponding high-resolution patches by using an ...
Jieying Zheng +3 more
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