7 days ago · In this paper, we focus on evaluating the impact of different data augmentation methods on the explainability of deep learning models used for medical image ...
8 days ago · Data augmentation is crucial for pixel-wise annotation tasks like semantic segmentation, where labeling requires significant effort and intensive labor.
Dec 15, 2024 · Data augmentation is a commonly used method for improving deep learning models in image classification. By adding slightly modified images that do not ...
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Dec 4, 2024 · Selecting pretrained models for image classification often involves computationally intensive finetuning. This study addresses a research gap in the ...
22 hours ago · Soft-diamond priors substantially improved accuracy on CIFAR-10 when combined with dropout, batch, or data-augmentation regularization.
Dec 16, 2024 · Softmax Function is typically used in the last layer of a neural network to predict the class of an input image. It is also used in other applications, such as ...
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4 days ago · This paper presents a policy-driven approach to augment training images for scene text recognition (STR). Image augmentation has been proven effective in ...
Dec 21, 2024 · By integrating soft labels with supervised labels, it captures the hidden category information of newly interpolated tasks, thereby reducing the impact of ...
5 days ago · This method automatically classifies pigmented skin disease images through a system architecture that includes image augmentation, image segmentation, cluster ...
Dec 3, 2024 · Machine-learning-based predictive maintenance models, i.e. models that predict breakdowns of machines based on condition information, have a high potential.