Zobrazeno 1 - 10
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pro vyhledávání: '"WEI, XING"'
Real-world image super-resolution (Real-ISR) has achieved a remarkable leap by leveraging large-scale text-to-image models, enabling realistic image restoration from given recognition textual prompts. However, these methods sometimes fail to recogniz
Externí odkaz:
http://arxiv.org/abs/2412.02960
Language-image pre-training faces significant challenges due to limited data in specific formats and the constrained capacities of text encoders. While prevailing methods attempt to address these issues through data augmentation and architecture modi
Externí odkaz:
http://arxiv.org/abs/2411.11927
Ensuring adherence to traffic sign regulations is essential for both human and autonomous vehicle navigation. While current benchmark datasets concentrate on lane perception or basic traffic sign recognition, they often overlook the intricate task of
Externí odkaz:
http://arxiv.org/abs/2410.23780
This study examines the quantile connectedness among grain futures markets in BRICS and international markets, with a particular focus on the ongoing and escalating impacts of the Russia-Ukraine conflict. The findings reveal significant heterogeneity
Externí odkaz:
http://arxiv.org/abs/2409.19307
Autor:
Wei, Si-yao, Zhou, Wei-xing
Resilience serves to assess the ability of financial markets to resist external shocks. The intensity and duration, used to indicate resilience, are calculated for China's financial markets in this paper, focusing on the performance of each financial
Externí odkaz:
http://arxiv.org/abs/2409.18422
Non-exemplar class Incremental Learning (NECIL) enables models to continuously acquire new classes without retraining from scratch and storing old task exemplars, addressing privacy and storage issues. However, the absence of data from earlier tasks
Externí odkaz:
http://arxiv.org/abs/2409.14983
This study investigates the relationships between agricultural spot markets and external uncertainties via the multifractal detrending moving-average cross-correlation analysis (MF-X-DMA). The dataset contains the Grains \& Oilseeds Index (GOI) and i
Externí odkaz:
http://arxiv.org/abs/2410.02798
High-Definition Maps (HD maps) are essential for the precise navigation and decision-making of autonomous vehicles, yet their creation and upkeep present significant cost and timeliness challenges. The online construction of HD maps using on-board se
Externí odkaz:
http://arxiv.org/abs/2409.05352
In this paper, we propose Neural Spectrum Decomposition, a generic decomposition framework for dataset distillation. Unlike previous methods, we consider the entire dataset as a high-dimensional observation that is low-rank across all dimensions. We
Externí odkaz:
http://arxiv.org/abs/2408.16236
Point cloud analysis has achieved significant development and is well-performed in multiple downstream tasks like point cloud classification and segmentation, etc. Being conscious of the simplicity of the position encoding structure in Transformer-ba
Externí odkaz:
http://arxiv.org/abs/2408.11567