Zobrazeno 1 - 10
of 797
pro vyhledávání: '"Zhang Letian"'
Publikováno v:
陆军军医大学学报, Vol 45, Iss 4, Pp 318-325 (2023)
Objective To evaluate the predictive value of apparent diffusion coefficient (ADC) histogram in preoperative magnetic resonance imaging (MRI) of the 2 cm peritumoral edema zone for spatial pattern of recurrence in IDH wild-type glioblastoma (GB). Met
Externí odkaz:
https://doaj.org/article/03e5c0cb024a46759f30668ed1e33103
Publikováno v:
Di-san junyi daxue xuebao, Vol 43, Iss 23, Pp 2577-2583 (2021)
Objective To explore the diagnostic values of different post-processing modes of dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) in the differentiation of glioma grade. Methods A total of 89 patients with glioma confirmed by postoperat
Externí odkaz:
https://doaj.org/article/0af90eda436742f9818cb9f035943cce
Foundation models (FMs) achieve strong performance across diverse tasks with task-specific fine-tuning, yet full parameter fine-tuning is often computationally prohibitive for large models. Parameter-efficient fine-tuning (PEFT) methods like Low-Rank
Externí odkaz:
http://arxiv.org/abs/2411.14961
Recent advancements in Deep Neural Networks (DNNs) have catalyzed the development of numerous intelligent mobile applications and services. However, they also introduce significant computational challenges for resource-constrained mobile devices. To
Externí odkaz:
http://arxiv.org/abs/2410.01857
The advancement of large language models (LLMs) has significantly broadened the scope of applications in natural language processing, with multi-modal LLMs extending these capabilities to integrate and interpret visual data. However, existing benchma
Externí odkaz:
http://arxiv.org/abs/2406.12742
Autor:
Ma, Wufei, Zeng, Guanning, Zhang, Guofeng, Liu, Qihao, Zhang, Letian, Kortylewski, Adam, Liu, Yaoyao, Yuille, Alan
A vision model with general-purpose object-level 3D understanding should be capable of inferring both 2D (e.g., class name and bounding box) and 3D information (e.g., 3D location and 3D viewpoint) for arbitrary rigid objects in natural images. This i
Externí odkaz:
http://arxiv.org/abs/2406.09613
Pre-trained vision-language models learn massive data to model unified representations of images and natural languages, which can be widely applied to downstream machine learning tasks. In addition to zero-shot inference, in order to better adapt pre
Externí odkaz:
http://arxiv.org/abs/2406.18550
Federated learning (FL) allows collaborative machine learning training without sharing private data. While most FL methods assume identical data domains across clients, real-world scenarios often involve heterogeneous data domains. Federated Prototyp
Externí odkaz:
http://arxiv.org/abs/2403.09048
Neural radiance fields (NeRF) is a promising approach for generating photorealistic images and representing complex scenes. However, when processing data sequentially, it can suffer from catastrophic forgetting, where previous data is easily forgotte
Externí odkaz:
http://arxiv.org/abs/2312.05748
Autor:
Zhang, Letian1 (AUTHOR) letian.lt.zhang@gmail.com, Wang, Shinan2 (AUTHOR)
Publikováno v:
Administrative Science Quarterly. Jun2024, Vol. 69 Issue 2, p417-457. 41p.