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Modality-aware Transformer for Financial Time series Forecasting
In practice, the key challenge lies in constructing a reliable time series forecasting model capable of harnessing data from diverse sources and extracting valuable insights to predict the target time series accurately.
SA-GAN: Structure-Aware GAN for Organ-Preserving Synthetic CT Generation
In medical image synthesis, model training could be challenging due to the inconsistencies between images of different modalities even with the same patient, typically caused by internal status/tissue changes as different modalities are usually obtained at a different time.
FREA-Unet: Frequency-aware U-net for Modality Transfer
While Positron emission tomography (PET) imaging has been widely used in diagnosis of number of diseases, it has costly acquisition process which involves radiation exposure to patients.
Attention-Guided Generative Adversarial Network to Address Atypical Anatomy in Modality Transfer
Recently, interest in MR-only treatment planning using synthetic CTs (synCTs) has grown rapidly in radiation therapy.
SPA-GAN: Spatial Attention GAN for Image-to-Image Translation
Image-to-image translation is to learn a mapping between images from a source domain and images from a target domain.
Generative Adversarial Network
Image-to-Image Translation
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