Results 11 to 20 of about 596,937 (313)
Pre-training Without Natural Images [PDF]
International Journal of Computer Vision, 2021 AbstractIs it possible to use convolutional neural networks pre-trained without any natural images to assist natural image understanding? The paper proposes a novel concept, Formula-driven Supervised Learning (FDSL). We automatically generate image patterns and their category labels by assigning fractals, which are based on a natural law. Theoretically,
Hirokatsu Kataoka +7 more
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Pre-Trained Image Processing Transformer [PDF]
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021 CVPR ...
Hanting Chen +9 more
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Masked Image Training for Generalizable Deep Image Denoising
2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023 Accepted to CVPR ...
Haoyu Chen 0003 +7 more
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Tensor-Train decomposition for image recognition [PDF]
Calcolo, 2020 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Brandoni D., Simoncini V.
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Image Augmentations for GAN Training
CoRR, 2020 Data augmentations have been widely studied to improve the accuracy and robustness of classifiers. However, the potential of image augmentation in improving GAN models for image synthesis has not been thoroughly investigated in previous studies. In this work, we systematically study the effectiveness of various existing augmentation techniques for GAN ...
Zhengli Zhao +4 more
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Informatics in Medicine Unlocked, 2020 Morphological analysis of white blood cells under a microscope is a crucial laboratory procedure for the diagnosis of several diseases including leukemia.
Mimosette Makem, Alain Tiedeu
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WG2AN: Synthetic wound image generation using generative adversarial network
The Journal of Engineering, 2021 In part due to its ability to mimic any data distribution, Generative Adversarial Network (GAN) algorithms have been successfully applied to many applications, such as data augmentation, text‐to‐image translation, image‐to‐image translation, and image ...
Salih Sarp +3 more
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Training for Multimodality Imaging [PDF]
European Journal of Nuclear Medicine and Molecular Imaging, 2012 A survey [2] was conducted in 2008 to obtain information on the status of multimodality equipment and procedures throughout Europe and to identify any visions on training for combined modalities. More than 75% of the respondents were in favour of joint development of an interdisciplinary training programme on a European level by the EANM and ESR. Fifty
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Effects of data count and image scaling on Deep Learning training [PDF]
PeerJ Computer Science, 2020 Background Deep learning using convolutional neural networks (CNN) has achieved significant results in various fields that use images. Deep learning can automatically extract features from data, and CNN extracts image features by convolution processing ...
Daisuke Hirahara +3 more
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Deep Learning-Based Plant-Image Classification Using a Small Training Dataset
Mathematics, 2022 Extensive research has been conducted on image augmentation, segmentation, detection, and classification based on plant images. Specifically, previous studies on plant image classification have used various plant datasets (fruits, vegetables, flowers ...
Ganbayar Batchuluun +2 more
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