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pro vyhledávání: '"Liu Huafeng"'
Dynamic positron emission tomography (PET) images can reveal the distribution of tracers in the organism and the dynamic processes involved in biochemical reactions, and it is widely used in clinical practice. Despite the high effectiveness of dynami
Externí odkaz:
http://arxiv.org/abs/2410.22674
Modeling and producing lifelike clothed human images has attracted researchers' attention from different areas for decades, with the complexity from highly articulated and structured content. Rendering algorithms decompose and simulate the imaging pr
Externí odkaz:
http://arxiv.org/abs/2410.14429
Time-of-flight (TOF) information provides more accurate location data for annihilation photons, thereby enhancing the quality of PET reconstruction images and reducing noise. List-mode reconstruction has a significant advantage in handling TOF inform
Externí odkaz:
http://arxiv.org/abs/2410.11148
Publikováno v:
Open Mathematics, Vol 19, Iss 1, Pp 1007-1017 (2021)
Let ff be a self-dual Hecke-Maass eigenform for the group SL3(Z)S{L}_{3}\left({\mathbb{Z}}). For 12
Externí odkaz:
https://doaj.org/article/90fa483de27e426b9ec3a54470494d80
Unsupervised semantic segmentation (USS) aims to achieve high-quality segmentation without manual pixel-level annotations. Existing USS models provide coarse category classification for regions, but the results often have blurry and imprecise edges.
Externí odkaz:
http://arxiv.org/abs/2405.11742
In dynamic positron emission tomography (PET) reconstruction, the importance of leveraging the temporal dependence of the data has been well appreciated. Current deep-learning solutions can be categorized in two groups in the way the temporal dynamic
Externí odkaz:
http://arxiv.org/abs/2403.07364
Modern applications increasingly require unsupervised learning of latent dynamics from high-dimensional time-series. This presents a significant challenge of identifiability: many abstract latent representations may reconstruct observations, yet do t
Externí odkaz:
http://arxiv.org/abs/2403.08194
Recently, the advancement of self-supervised learning techniques, like masked autoencoders (MAE), has greatly influenced visual representation learning for images and videos. Nevertheless, it is worth noting that the predominant approaches in existin
Externí odkaz:
http://arxiv.org/abs/2402.19082
Learning with noisy labels has gained increasing attention because the inevitable imperfect labels in real-world scenarios can substantially hurt the deep model performance. Recent studies tend to regard low-loss samples as clean ones and discard hig
Externí odkaz:
http://arxiv.org/abs/2402.11242
Glioblastoma is one of the most aggressive and deadliest types of brain cancer, with low survival rates compared to other types of cancer. Analysis of Magnetic Resonance Imaging (MRI) scans is one of the most effective methods for the diagnosis and t
Externí odkaz:
http://arxiv.org/abs/2312.11467