Zobrazeno 1 - 10
of 41 292
pro vyhledávání: '"An, Haixia"'
Autor:
Cai, Xiaofan, Chen, Ruichang, Gao, Xu, Yuan, Meili, Hu, Haixia, Yin, Hang, Qu, Yuanyuan, Tan, Yang, Chen, Feng
Recently, avalanche multiplication has been observed in TMDC-based FETs, enhancing sensor performance with high sensitivity. However, the high voltage required for operation can damage the FETs, making it crucial to reduce the breakdown voltage for e
Externí odkaz:
http://arxiv.org/abs/2409.07677
Accurate classification of port wine stains (PWS, vascular malformations present at birth), is critical for subsequent treatment planning. However, the current method of classifying PWS based on the external skin appearance rarely reflects the underl
Externí odkaz:
http://arxiv.org/abs/2408.16277
Nonlinear circuits serve as crucial carriers and physical models for investigating nonlinear dynamics and chaotic behavior, particularly in the simulation of biological neurons. In this study, Chua's circuit and Lorenz circuit are systematically expl
Externí odkaz:
http://arxiv.org/abs/2408.16972
Segment Anything Model (SAM) has demonstrated impressive performance on a wide range of natural image segmentation tasks. However, its performance significantly deteriorates when directly applied to medical domain, due to the remarkable differences b
Externí odkaz:
http://arxiv.org/abs/2408.09886
By developing a unified approach based on integral representations, we establish sharp quantitative stability estimates for critical points of the fractional Sobolev inequalities induced by the embedding $\dot{H}^s({\mathbb R}^n) \hookrightarrow L^{2
Externí odkaz:
http://arxiv.org/abs/2408.07775
The annotation of polarimetric synthetic aperture radar (PolSAR) images is a labor-intensive and time-consuming process. Therefore, classifying PolSAR images with limited labels is a challenging task in remote sensing domain. In recent years, self-su
Externí odkaz:
http://arxiv.org/abs/2408.04294
Due to the effective performance of multi-scale feature fusion, Path Aggregation FPN (PAFPN) is widely employed in YOLO detectors. However, it cannot efficiently and adaptively integrate high-level semantic information with low-level spatial informat
Externí odkaz:
http://arxiv.org/abs/2407.04381
Traditional regression and prediction tasks often only provide deterministic point estimates. To estimate the uncertainty or distribution information of the response variable, methods such as Bayesian inference, model ensembling, or MC Dropout are ty
Externí odkaz:
http://arxiv.org/abs/2406.11397
In this paper, we present a convergence analysis of the Group Projected Subspace Pursuit (GPSP) algorithm proposed by He et al. [HKL+23] (Group Projected subspace pursuit for IDENTification of variable coefficient differential equations (GP-IDENT), J
Externí odkaz:
http://arxiv.org/abs/2407.07707
Autor:
Luo, Ziqin, Han, Haixia, Zhao, Haokun, Jiang, Guochao, Du, Chengyu, Li, Tingyun, Liang, Jiaqing, Yang, Deqing, Xiao, Yanghua
Existing Large Language Models (LLMs) generate text through unidirectional autoregressive decoding methods to respond to various user queries. These methods tend to consider token selection in a simple sequential manner, making it easy to fall into s
Externí odkaz:
http://arxiv.org/abs/2405.16552