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pro vyhledávání: '"XIE, Bin"'
In general class-incremental learning, researchers typically use sample sets as a tool to avoid catastrophic forgetting during continuous learning. At the same time, researchers have also noted the differences between class-incremental learning and O
Externí odkaz:
http://arxiv.org/abs/2408.08084
The objective of this work is to investigate the utility and effectiveness of the high-order scheme for simulating unsteady turbulent flows. To achieve it, the studies were conducted from two perspectives: (i) the ability of different numerical schem
Externí odkaz:
http://arxiv.org/abs/2407.19764
In this paper, wall-modeled large-eddy simulation (WMLES) is carried out with Ffowcs-Williams and Hawkings (FW-H) acoustic analogy to investigate the turbulent flow and hydrodynamic noise of an axisymmetric body of revolution. We first develop the nu
Externí odkaz:
http://arxiv.org/abs/2407.10475
Segment Anything Model~(SAM), a prompt-driven foundation model for natural image segmentation, has demonstrated impressive zero-shot performance. However, SAM does not work when directly applied to medical image segmentation tasks, since SAM lacks th
Externí odkaz:
http://arxiv.org/abs/2403.14103
Open-vocabulary semantic segmentation strives to distinguish pixels into different semantic groups from an open set of categories. Most existing methods explore utilizing pre-trained vision-language models, in which the key is to adopt the image-leve
Externí odkaz:
http://arxiv.org/abs/2311.15537
Benefiting from the rapid development of deep learning, 2D and 3D computer vision applications are deployed in many safe-critical systems, such as autopilot and identity authentication. However, deep learning models are not trustworthy enough because
Externí odkaz:
http://arxiv.org/abs/2310.00633
How to accurately measure the relevance and redundancy of features is an age-old challenge in the field of feature selection. However, existing filter-based feature selection methods cannot directly measure redundancy for continuous data. In addition
Externí odkaz:
http://arxiv.org/abs/2307.14643
Autor:
XIE Bin1 xiebinsilicon@foxmail.com, REN Tingting1
Publikováno v:
Chinese Journal of Immunology. May2024, Vol. 40 Issue 5, p981-991. 11p.
Denoising diffusion (score-based) generative models have recently achieved significant accomplishments in generating realistic and diverse data. These approaches define a forward diffusion process for transforming data into noise and a backward denoi
Externí odkaz:
http://arxiv.org/abs/2211.15736
Autor:
Kember, Pamela
Publikováno v:
Benezit Dictionary of Asian Artists, 1 ed., 2013.